Journal of Epidemiology and Community Health

ObjectiveTo estimate the risk of Long COVID by socioeconomic deprivation and to further examine the socioeconomic inequalities in Long COVID by sex and occupational groups. DesignWe analysed data from the COVID-19 Infection Survey conducted by the Office for National Statistics between 26/04/2020 and 31/01/2022. This is the largest and nationally representative survey of COVID-19 in the UK and provides uniquely rich, contemporaneous, and longitudinal data on occupation, health status, COVID-19 exposure, and Long COVID symptoms. SettingCommunity-based longitudinal survey of COVID-19 in the UK. ParticipantsWe included 201,799 participants in our analysis who were aged between 16 and 64 years and had a confirmed SARS-CoV-2 infection. Main outcome measuresWe used multivariable logistic regression models to estimate the risk of Long COVID at least 4 weeks after acute SARS-CoV-2 infection by deciles of index of multiple deprivation (IMD) and adjusted for a range of demographic and spatiotemporal factors. We further examined the modifying effects of socioeconomic deprivation by sex and occupational groups. ResultsA total of 19,315 (9.6%) participants reported having Long COVID symptoms. Compared to the least deprived IMD decile, participants in the most deprived decile had a higher adjusted risk of Long COVID (11.4% vs 8.2%; adjusted OR: 1.45; 95% confidence interval [CI]: 1.33, 1.57). There were particularly significantly higher inequalities (most vs least deprived decile) of Long COVID in healthcare and patient facing roles (aOR: 1.76; 1.27, 2.44), and in the education sector (aOR: 1.62; 1.26, 2.08). The inequality of Long COVID was higher in females (aOR: 1.54; 1.38, 1.71) than males (OR: 1.32; 1.15, 1.51). ConclusionsParticipants living in the most socioeconomically deprived areas had a higher risk of Long COVID. The inequality gap was wider in females and certain public facing occupations (e.g., healthcare and education). These findings will help inform public health policies and interventions in adopting a social justice and health inequality lens.

BackgroundHealth inequalities in Scotland are well documented, including the contribution of different causes to inequalities in mortality. Our aim was to estimate inequalities within a burden of disease framework, accounting for both premature mortality and the effects of morbidity, to understand the contribution of specific diseases to health inequalities prior to the COVID-19 pandemic. MethodsDisability Adjusted Life Years (DALYs) for 70 individual causes of disease and injury were sourced from the Scottish Burden of Disease Study. Area-level deprivation was measured using the Scottish Index of Multiple Deprivation. Inequalities were measured by the range, Relative Index of Inequality, Slope Index of Inequality, and attributable DALYs were estimated by using the least deprived decile as a reference. ResultsThe overall disease burden was double that in the most deprived areas (50,305 vs 20,955 DALYS per 100, 000), largely driven by inequalities in premature mortality. The rate in the most deprived decile was around 48% higher than the mean population rate (RII = 0.96), with 35% of DALYs attributed to differences in area-based deprivation. Many leading causes of disease burden in 2019 - heart disease, drug use disorders, lung cancer and COPD - were also the leading drivers of absolute and relative inequalities in the disease burden. ConclusionOur study evidences the extent of the stark levels of absolute and relative inequality prior to the COVID-19 pandemic. Given pre-pandemic stalling of mortality trend improvements and widening health inequalities, and the exacerbation of these caused by COVID-19, urgent policy attention is required to address this.

Background Health inequalities between occupational or social class groups are pervasive and persistent. Healthcare professionals have better health outcomes compared to the general population. Whether this is a result of healthcare education, favourable socio-demographic characteristics among professionals or other effects is not certain and the extent to which single healthcare occupational groups exhibit inequalities is unknown. We have described self-rated health and quantified geographic health inequalities among a single occupational group of Registered Nurses compared to the general population. Methods We analysed nationally representative samples from the 2011 UK Censuses across England, Wales and Scotland in the Office for National Statistics Longitudinal Study and Scottish Longitudinal Study. Self-rated health and socio-demographic characteristics for the study population are described. Inequalities in health by area deprivation among Registered Nurses and the General Population are quantified. Logistic regression analysis was used to assess the association between Nurse status and self-rated health, adjusting for socio-demographic variables. Results Among economically active, working age adults (n = 478,802), we identified 9,180 Registered Nurses resident in England, Wales and Scotland. 59% of Registered Nurses reported very good self-rated health, with only 1% reporting poor or very poor health. A smaller proportion of Registered Nurses reported less than good health than the General Population at every level of area deprivation and had smaller absolute (4.1 percentage points vs. 9.1) and relative (RR: 1.5 vs. 2.0) inequalities between residents in the most and least deprived areas. Registered Nurses have an increased likelihood of reporting good or better health compared to the general population (Scotland OR: 1.3, 95% CI: 1.2 - 1.5, England & Wales OR: 1.4, 95% CI: 1.3 - 1.5) after adjusting for socio-demographic factors. Discussion Registered Nurses report better health compared to the general population and have smaller inequalities in health by area deprivation. However, unfair and avoidable geographical differences in health are present even in this socioeconomically privileged professional group. After adjusting for socioeconomic and demographic factors, the positive association between being a Registered Nurse and having good self-rated health remained.

BackgroundYoung people who are not in education, employment or training (NEET) are at an increased risk of long-term social and economic disadvantage. While previous research has linked various risk factors and individual characteristics to NEET status, evidence on the cumulative impact of early-life exposure to childhood adversity in the UK remains limited. MethodsWe analysed longitudinal data on 8,368 participants from the UK Millennium Cohort Study. Using group-based multi-trajectory modelling approach, we identified six distinct exposure trajectories of poverty and family adversity (including poor parental mental health, domestic violence and abuse and alcohol use) from aged 9 months to 14 years. NEET status was assessed at age 17. Adjusted odds ratios (aORs) and 95% CIs were estimated using logistic regression models. Population attributable fractions (PAFs) were calculated to estimate the proportion of NEET cases attributable to childhood poverty and family adversity. ResultsOverall, 3.5% of participants were NEET at age 17 years. NEET status was more prevalent among young people from socially disadvantaged backgrounds than their peers. Exposure to persistent family childhood adversities was associated with greater likelihood of being NEET. Young people exposed to both persistent poverty and poor parental mental health throughout childhood (0-14 years) had five times greater odds of being NEET (adjusted odds ratio [aOR] 5.0; 95% CI 3.4-7.5) compared to those in low poverty and adversity. An estimated 52.9% (95% CI: 41.1-61.7) of NEET cases were attributable to persistent exposure to poverty and family adversity. ConclusionFamily childhood adversities, particularly household poverty and poor parental mental health are strongly associated with an increased risk of being NEET on transition to adulthood. Interventions that address early-life socio-economic disadvantage and family functioning may be critical for preventing NEET and mitigating its long-term social and economic consequences. What is already known on this topicO_LIYoung people who are not in education, employment or training (NEET) are at risk of poor health, social exclusion and long-term economic disadvantage. C_LIO_LIChildhood poverty and family adversity have been associated with NEET status, but their cumulative and life-course impact in the UK remains unclear. C_LI What this study addsO_LIUsing longitudinal data from a nationally representative UK cohort, this study shows that persistent exposure to poverty and family childhood adversity including poor parental mental health increase the likelihood of being NEET at age 17. C_LIO_LIIndividuals exposed to multiple family childhood adversity (i.e., poverty and poor parental mental health) were five times more likely to be NEET. C_LIO_LIAn estimated 52.9% NEET cases were attributable to persistent poverty and family childhood adversity. C_LI How this study might affect research, policy, or practiceO_LIInterventions that address family childhood adversity, particularly household poverty and poor parental mental health could substantially reduce NEET prevalence and mitigate long-term inequalities. C_LI

BackgroundThere is a growing concern about the increasing number of young people who are not in employment, education or training (NEET) globally. This study investigates the impact of concurrent cognitive and socioemotional development trajectories in childhood on NEET status in adolescence in a UK cohort. MethodWe analysed longitudinal data on 8,368 children from the UK Millennium Cohort Study. Exposure trajectories of cognitive and socioemotional development from age 3 to 14 years were characterised using group-based multi-trajectory models. We used Poisson regression to examine associations between developmental trajectories and NEET status at age 17, adjusting for confounders. Population-attributable fractions were estimated to quantify NEET proportions attributable to the developmental problems. ResultsAt age 17, 3.5% of participants were NEET; of which about one-third (38%) were not economically active. Children with persistent cognitive and socioemotional development problems had a fourfold increased risk of being NEET (adjusted risk ratio [ARR] 4.0; 95% CI 2.5-6.3), and those with late socioemotional problems had threefold increased risk (3.3; 95% CI 2.2-4.9), compared to children in the no problem group. Early and resolving socioemotional and cognitive problems were not associated with being NEET. An estimated 28% (95% CI 18% to 36%) of NEET cases were attributable to cognitive and socioemotional behaviour problems in childhood. ConclusionChildhood cognitive and socioemotional development play a critical role in shaping pathways to education and employment in adolescence. Thus, policies and strategies aiming to reduce NEET should target early social and emotional skills, alongside efforts to support academic achievement. Strengths and limitations of this study{blacksquare} The study uses longitudinal data from a contemporary and representative cohort of UK children. {blacksquare}The study combines measures of cognitive ability and socioemotional behaviour during childhood, and evaluates the joint effects on youth NEET status {blacksquare}A major limitation was inability to capture transitions in the NEET status as it was measured at a single time point {blacksquare}As with most longitudinal cohort studies, missing data is inevitable and hence a challenge for analysis.

BackgroundPost-COVID Condition (PCC) is increasingly recognised to impair daily functioning, particularly work ability, cognitive function, and self-care. This analysis investigates the role of deprivation, migration status, and ethnicity in experiencing limitations in six functional activities: work/education, concentration, self-care, caring for others, performing necessary activities outside the house, and engaging in enjoyable activities. MethodsWe analysed data from Virus Watch, a prospective community cohort study in England, identifying 776 individuals ([≥]18 years) with PCC between February 2020 and March 2024. We used logistic regression to assess how deprivation, migration and ethnic minority status were associated with the odds of experiencing each functional limitation, adjusting for sociodemographic variables. FindingsIndividuals with PCC in IMD 1 (the most deprived quintile) had higher adjusted odds of limitations in work/education, concentration, self-care, and doing necessary activities outside the house than those in IMD 5 (the least deprived) (adjusted odds ratio (aOR) range: 2{middle dot}20-2{middle dot}85). Those in IMD 2 also experienced increased odds of limitations in work/education and concentration compared to those in IMD 5. We found no evidence of associations between migration status or minority ethnicity with functional limitations among PCC individuals. InterpretationOur findings indicate that socioeconomic deprivation, rather than migration status or ethnicity, is the primary driver of functional limitations within this cohort. Functional limitations may perpetuate cycles of deprivation and further exacerbate health inequalities. Equitable access to rehabilitation and support services, alongside workplace and educational adaptations, is needed to address the functional limitations of those affected by PCC. FundingMedical Research Council; Wellcome Trust; European Union Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and Web of Science for English-language articles indexed from March 2020 up to May 2025 on the association between deprivation, migration status, and ethnicity, and functional limitations of post-COVID condition (PCC). The search string ("post-COVID condition" OR "long COVID" OR "post-acute COVID-19" OR "post-COVID syndrome" OR "post-acute sequelae of SARS-CoV-2" OR PCC) AND (deprivation OR "Index of Multiple Deprivation" OR IMD OR "socioeconomic status" OR "social determinants" OR "social inequality" OR migration OR "migration status" OR migrant OR immigrant OR ethnicity OR "ethnic minority" OR race OR "racial group") AND ("functional limitation*" OR "functional impairment*" OR "activity limitation*" OR "participation restriction*" OR "functional status" OR "work ability" OR "work attendance" OR "school attendance" OR "work participation" OR "school participation" OR concentration OR "cognitive impairment" OR "brain fog" OR "self-care" OR "activities of daily living" OR ADL OR "caring for others" OR caregiving OR "leisure activities" OR "enjoyable activities" OR "social participation" OR "necessary activities outside the house" OR "instrumental activities of daily living" OR IADL) was used. The search identified several US-based studies reporting greater functional limitations among Black and Hispanic populations, but few data exist outside the US, and none addressed deprivation and migration status. We therefore excluded the search terms related to social determinants in a follow-up search to focus on the broader literature on functional limitations. Most studies focused on hospitalised populations and often lacked detail on specific functional activities. One UK-based study reported greater functional impairment, measured using the Work and Social Adjustment Scale, among individuals in the most deprived quintile compared to those in less deprived quintiles in the UK. However, the impact of migration status remains largely unexplored. Added value of this studyTo our knowledge, this is the first study to examine how deprivation, migration status, and ethnic minority status influence specific functional limitations among adults with PCC in England. By disaggregating specific daily activities, we found that individuals living in more deprived areas experience greater odds of limitations in work/education attendance or participation, concentration, self-care, and doing necessary activities outside the house compared to those living in the least deprived areas. In contrast, no disparities were observed for migrants or ethnic minorities. Our findings provide granular insights into the role of social determinants, particularly deprivation, in influencing the functional impacts of PCC, allowing the development of more targeted interventions and policy responses to support those most affected. Implications of all the available evidenceAlongside existing evidence, our findings highlight the need for targeted interventions to address the disproportionate impact of PCC on individuals in deprived communities. Policy responses should prioritise equitable access to rehabilitation and support services through adapted referral pathways and culturally appropriate outreach. Reforming statutory sick pay eligibility and ensuring the availability of flexible workplace or educational arrangements should also be ensured for those affected. Addressing these systemic barriers will prevent further widening of health inequalities and support a more equitable recovery from the long-term effects of COVID-19, while also informing future public health strategies for post-acute conditions.

Ethnic minority populations faced a disproportionate impact of the COVID-19 pandemic. Loneliness, a significant public health issue, was exacerbated during the pandemic. Most previous studies used aggregated ethnic groups and overlooked underrepresented groups. This study explored ethnic inequalities in loneliness across 21 disaggregated ethnic groups in Britain during the COVID-19 pandemic. It used cross-sectional data (February to November 2021) from the Evidence for Equality National Survey (EVENS), with 14215 participants aged 18-75 from 21 ethnic groups in Britain. Weighted logistic regression models examined ethnic inequalities in loneliness across 21 disaggregated and 6 aggregated groups, both unadjusted and adjusted for socio-demographics. This study found higher odds of loneliness among most ethnic minority groups, with nuanced differences that were overlooked in aggregated analyses. Socio-demographics explained disparities for some ethnic groups, while differences in others remained after adjustment, suggesting additional factors driving these differences.

IntroductionSocioeconomic position has been strongly associated with cardiovascular health. However, little is known about the short-term health impacts of socioeconomic exposures during early adulthood. In this study we describe distinct socioeconomic trajectories of early adulthood (age 16-24y), and assess associations of these trajectories with measures of cardiometabolic health at age 24y. MethodsParticipants of the Avon Longitudinal Study of Parents and Children (ALSPAC), with data across age 16y to 24y (2007-2017) were included (n=7,568). Longitudinal latent class analysis identified socioeconomic trajectories, based on education and employment data across ages 16-24y. Cardiometabolic outcomes at age 24y comprised anthropometric, vascular, metabolic and cardiovascular structure and function measures. We modelled differences in cardiometabolic outcomes at age 24y across the socioeconomic trajectory classes, adjusting for childhood socioeconomic position, adolescent health behaviours and adolescent health. ResultsFour early adulthood socioeconomic trajectories were identified: (1) Higher Education (41% of the population), (2) Extended Education (9%), (3) Part-Time Employment (21%), and (4) Early Employment (29%). Associations between socioeconomic trajectory and cardiometabolic outcomes differed by sex. Among males, the Higher Education and Extended Education classes showed a healthier cardiometabolic profile, and the Part-time Employment class the least healthy. Among females there was less clear distinction between the classes, and the pattern across different outcomes was not consistent. ConclusionThe newly identified Part-time Employment class showed the least healthy cardiometabolic profile, and further research should focus on this group to understand the exposures contributing to poor cardiometabolic health in this sector of the population.

BackgroundHome working rates have increased since the COVID-19 pandemics onset, but the health implications of this transformation are unclear. We assessed the association between home working and social and mental wellbeing through harmonised analyses of seven UK longitudinal studies. MethodsWe estimated associations between home working and measures of psychological distress, low life satisfaction, poor self-rated health, low social contact, and loneliness across three different stages of the COVID-19 pandemic (T1= Apr-Jun 2020 - first lockdown, T2=Jul-Oct 2020 - eased restrictions, T3=Nov 2020-Mar 2021 - second lockdown), in seven population-based cohort studies using modified Poisson regression and meta-analyses to pool results across studies. FindingsAmong 34,131 observations spread over three time points, we found higher rates of home working at T1 and T3 compared with T2, reflecting lockdown periods. Home working was not associated with psychological distress at T1 (RR=0.92, 95%CI=0.79-1.08) or T2 (RR=0.99, 95%CI=0.88-1.11), but a detrimental association was found with psychological distress at T3 (RR=1.17, 95%CI=1.05-1.30). Poorer psychological distress associated with home working was observed for those educated to below degree level at T2 and T3. Men working from home reported poorer self-reported health at T2. InterpretationNo clear evidence of an association between home working and mental wellbeing was found, apart from greater risk of psychological distress associated with home working during the second lockdown, but differences across sub-groups may exist. Longer term shifts to home working might not have adverse impacts on population wellbeing in the absence of pandemic restrictions but further monitoring of health inequalities is required. FundingNational Core Studies, funded by UKRI, NIHR and the Health and Safety Executive.

ObjectivesTo undertake a preliminary hypothesis-generating analysis exploring putative risk factors for coronavirus diseae 2019 (COVID-19) population-adjusted deaths, compared with non-COVID-19 related deaths, at a local authority district (LAD) level in hospital, care homes and at home. DesignEcological retrospective cohort study SettingLocal authority districts (LADs) in England, Scotland and Wales (Great Britain (GB)). ParticipantsAll LAD deaths registered by week 16 of 2020. Main Outcome MeasuresDeath registration where COVID-19 is mentioned as a contributing factor per 100,000 people in all settings, and in i) cares homes, ii) hospitals or iii) home only, in comparison to non-COVID-19 related deaths. ResultsAcross GB by week 16 of 2020, 20,684 deaths had been registered mentioning COVID-19, equivalent to 25.6 per 100,000 people. Significant risk factors for LAD COVID-19 death in comparison to non-COVID-19 related death were air pollution and proportion of the population who were female. Significant protective factors were higher air temperature and proportion of the population who were ex-smokers. Conversely, for all COVID-19 unrelated deaths in comparison to COVID-19 deaths, higher rates of communal living, higher population rates of chronic kidney disease, chronic obstructive pulmonary disease, cerebrovascular disease deaths under 75 and dementia were predictive of death, whereas, higher rates of flight passengers was protective. Looking at individual setttings, the most notable findings in care homes was Scotland being a significant risk factor for COVID-19 related deaths compared to England. For hospital setting, the proportion of the population who were from black and Asian minority ethnic (BAME) groups significantly predicted COVID-19 related death. ConclusionsThis is the first study within GB to assess COVID-19 related deaths in comparison to COVID-19 unrelated deaths across hospital, care homes and home combined. As an ecological study, the results cannot be directly extrapolated to individuals. However, the analysis may be informative for public health policy and protective measures. From our hypothesis-generating analysis, we propose that air pollution is a significant risk factor and high temperature a significant protective factor for COVID-19 related deaths. These factors cannot readily be modelled at an individual level. Scottish local authorities and local authorities with a higher proportion of individuals of BAME origin are potential risk factors for COVID-19 related deaths in care homes and in hospitals, respectively. Altogether, this analysis shows the benefits of access to high quality open data for public information, public health policy and further research.

BackgroundStructural barriers to testing may introduce selection bias in COVID-19 research. We explore whether changes to testing and lockdown restrictions introduce time-specific selection bias into analyses of socioeconomic position (SEP) and SARS-CoV-2 infection. MethodsUsing UK Biobank (N = 420 231; 55 % female; mean age = 56{middle dot}3 [SD=8{middle dot}01]) we estimated the association between SEP and i) being tested for SARS-CoV-2 infection versus not being tested ii) testing positive for SARS-CoV-2 infection versus testing negative and iii) testing negative for SARS-CoV-2 infection versus not being tested, at four distinct time-periods between March 2020 and March 2021. We explored potential selection bias by examining the same associations with hypothesised positive (ABO blood type) and negative (hair colour) control exposures. Finally, we conducted a hypothesis-free phenome-wide association study to investigate how individual characteristics associated with testing changed over time. FindingsThe association between low SEP and SARS-CoV-2 testing attenuated across time-periods. Compared to individuals with a degree, individuals who left school with GCSEs or less had an OR of 1{middle dot}05 (95% CI: 0{middle dot}95 to 1{middle dot}16) in March-May 2020 and 0{middle dot}98 (95% CI: 0{middle dot}94 to 1{middle dot}02) in January-March 2021. The magnitude of the association between low SEP and testing positive for SARS-CoV-2 infection increased over the same time-period. For the same comparisons, the OR for testing positive increased from 1{middle dot}27 (95% CI: 1{middle dot}08 to 1{middle dot}50), to 1{middle dot}73 (95% CI: 1{middle dot}59 to 1{middle dot}87). We found little evidence of an association between both control exposures and all outcomes considered. Our phenome-wide analysis highlighted a broad range of individual traits were associated with testing, which were distinct across time-periods. InterpretationThe association between SEP (and indeed many individual traits) and SARS-CoV-2 testing changed over time, indicating time-specific selection pressures in COVID-19. However, positive, and negative control analyses suggest that changes in the magnitude of the association between SEP and SARS-CoV-2 infection over time were unlikely to be explained by selection bias and reflect true increases in socioeconomic inequalities. FundingUniversity of Bristol; UK Medical Research Council; British Heart Foundation; European Union Horizon 2020; Wellcome Trust and The Royal Society; National Institute of Health Research; UK Economic and Social Research Council

BackgroundNeighbourhood environments may influence cardiovascular disease (CVD) risk, e.g. by influencing diet and physical activity (PA) behaviours. We explored whether associations between characteristics of neighbourhood environments and CVD are modified by area deprivation and household income. If effects of neighbourhood risk exposures vary by socioeconomic position, efforts to improve population health by improving neighbourhood built environments could widen health inequalities. MethodsIn the UK Biobank cohort we used linked records of hospital admissions to assess the relative hazard of being admitted to hospital with a primary diagnosis of CVD according to three characteristics of the neighbourhood built environment: availability of formal PA facilities, proximity of a takeaway/fast-food store, and neighbourhood greenspace. We then examined potential effect modification of the main associations by household income and area deprivation. We used Cox proportional hazards models, adjusted for likely confounding, and calculated relative excess risks due to interaction (RERI) to assess effect modification on the additive scale. We also examined the combined modifying role of income and deprivation. ResultsThere were 13,809 incident CVD admissions in the sample (mean follow-up=6.8 years). Overall associations between neighbourhood exposures and CVD-related hospital admissions were weak to null. However, there was evidence of effect modification by both area deprivation and household income. Greater availability of PA facilities near home was associated with lower risk of CVD-related admission in more deprived areas, but only among people in higher-income households. Area deprivation and household income both modified the association with fast-food proximity. More greenspace was not associated with lower risk of CVD-related admission for any group. Some results differed between women and men. Findings were largely robust to alternative model specifications. ConclusionsImproving deprived neighbourhoods by increasing the number of PA facilities, while also ensuring access to these is free or affordable, may improve population health. Examining effect modification by multiple socioeconomic indicators in parallel can yield deeper insight into how different aspects of the peoples socioeconomic conditions influence their relationship with the built environment and its effects on their health. Improved understanding may help to avoid generating or perpetuating health inequalities when neighbourhood-based built environment interventions are designed.

BackgroundThere are concerns that mortality remains elevated after peaks COVID-19. This study examined whether mortality rates in England and Scotland in 2022 were excessive compared to rates predicted by austerity-era (2012-2019) and pre-austerity (2001-2010) trends. MethodsA linear time trend analysis was conducted using mortality data from 2001-2022. The outcomes were observed and expected age- and sex-standardised mortality rates (ASMRs; standardised to the 2013 European Standard Population). Expected ASMRs in 2022 were calculated independently based on austerity-era and pre-austerity trends. Excess deaths were estimated by comparing observed and expected ASMRs. ResultsIn 2022, ASMRs were higher than predicted by austerity-era trends but substantially higher than pre-austerity trends. Relative excesses in England for females were 4.4% (4.0-4.8) and 38.2% (95% CI: 37.7-38.7), respectively; for males, excesses were 7.2% (6.8-7.6) and 57.0% (56.4-57.6). Relative excesses in Scotland for females were 3.4% (2.2-4.5) and 26.6% (25.2-28.0); for males, excesses were 2.6% (1.5-3.8) and 45.2% (43.6-46.9). COVID-19 accounted for 5.3-6.5% of deaths in 2022 and explained much of the excess relative to austerity-era trends. ASMRs in the most deprived areas were 1.68-1.94 times higher than in the least deprived. ConclusionMortality was higher than predicted by both austerity-era and pre-austerity trends. Deaths attributable to COVID-19 explain a substantial proportion of the excess based on austerity-era trends. However, the 879,430 excess deaths relative to pre-austerity trends, even after excluding direct COVID-19 deaths, highlights the devastating impacts of austerity on public health. KEY MESSAGESO_ST_ABSWhat is already known on this topic?C_ST_ABSMortality in England and Scotland remained elevated following the peaks of 2020 and 2021 caused by COVID-19, indicating a further worsening of the unprecedented stalling of mortality rates observed from around 2012. What this study addsWhile COVID-19 explained much of the 2022 excess mortality relative to projections based on austerity-era trends, far greater excesses emerged when compared to projections based on the consistent decline in mortality observed prior to austerity. How this study might affect research, practice or policyThese findings highlight the profound, long-term harm of austerity, particularly in deprived areas, with an estimated 879,430 excess deaths between 2013 and 2022. The study strengthens calls for urgent policy action to reverse austeritys effects and reduce health inequalities.

The health benefits of regular physical activity in adolescence are well-documented. Many health-related behaviours and lifestyle choices are established in adolescence. The neighbourhood environment is a key setting for physical activity in adolescence and feeling unsafe in their neighbourhood may be a potential barrier to physical activity. This study aimed to examine associations between neighbourhood safety and physical activity using objective and subjective measures for both. Participants (n=10,913) came from the Millennium Cohort Study, a nationally representative UK longitudinal birth cohort. Results indicate that feeling unsafe in the neighbourhood, IMD crime and violent crime are barriers to physical activity participation in adolescents.

BackgroundHousing insecurity is an escalating problem in the UK but there is limited evidence about its health impacts. Using nationally representative panel data and causally focussed methods, we examined the effect of insecure housing on mental health, sleep and blood pressure, during a period of government austerity. MethodsWe used longitudinal survey data (2009-2019) from the UK Household Longitudinal Study. Outcomes were probable common mental disorder, sleep disturbance due to worry, and new diagnoses of hypertension. The primary exposure was housing payment problems in the past year. Using doubly robust marginal structural models with inverse probability of treatment weights, we estimated absolute and relative health effects of housing payment problems, and population attributable fractions. In stratified analyses we assessed potentially heterogeneous impacts across the population, and potential modifying effects of government austerity measures. A negative control analysis was conducted to detect bias due to unmeasured confounding. ResultsHousing payment problems were associated with a 2.5 percentage point increased risk of experiencing a common mental disorder (95% CI 1.1%, 3.8%) and 2.0% increased risk of sleep disturbance (95% CI 0.7%, 3.3%). Estimates were larger for renters, younger people, less educated, households with children, and people living in areas most affected by austerity-related cuts to housing support services. We did not find consistent evidence for an association with hypertension (RD=0.6%; 95% CI -0.1%, 1.2%). The negative control analysis was not indicative of unmeasured confounding. ConclusionsHousing payment problems were associated with worse mental health and sleep disturbance in a large UK sample. Households at risk of falling into rent or mortgage arrears need more support, especially in areas where housing support services have been diminished. Substantial investment is urgently needed to improve supply of social and affordable housing.

ObjectivesTo assess variation in vaccination uptake across occupational groups as a potential explanation for variation in risk of SARS-CoV-2 infection. DesignWe analysed data from the UK Office of National Statistics COVID-19 Infection Survey linked to vaccination data from the National Immunisation Management System in England from December 1st 2020 to 11th May 2022. We analysed vaccination uptake and SARS-CoV-2 infection risk by occupational group and assessed whether adjustment for vaccination reduced the variation in risk between occupational groups. Setting ResultsEstimated rates of triple-vaccination were high across all occupational groups (80% or above), but were lowest for food processing (80%), personal care (82%), hospitality (83%), manual occupations (84%), and retail (85%). High rates were observed for individuals working in health (95% for office-based, 92% for those in patient-facing roles) and education (91%) and office-based workers not included in other categories (90%). The impact of adjusting for vaccination when estimating relative risks of infection was generally modest (ratio of hazard ratios reduced from 1.38 to 1.32), but was consistent with the hypothesis that low vaccination rates contribute to elevated risk in some groups. Conversely, estimated relative risk for some occupational groups, such as people working in education, remained high despite high vaccine coverage. ConclusionsVariation in vaccination coverage might account for a modest proportion of occupational differences in infection risk. Vaccination rates were uniformly very high in this cohort, which may suggest that the participants are not representative of the general population. Accordingly, these results should be considered tentative pending the accumulation of additional evidence.

The SARS-CoV-2 pandemic had a large impact on social mixing in the UK. This study analysed data from the Office for National Statistics Coronavirus Infection Survey to examine changes in contact patterns and self-reported symptoms through three winter seasons from 2020 to 2023. Using Generalised Additive Models, we estimated levels of various contacts over time, accounting for age, sex, ethnicity, and deprivation percentile, and compared these to trends in self-reported symptoms. Our estimates indicated steady increases in physical contacts from quarter-4 2020 to the end of the study in quarter-1 2023, with notable variation in age-specific trends. School closures and holiday periods had substantial impacts on contact patterns, particularly for children. Prevalence of reported symptoms also increased steadily over time, but varied much more within-season than most contacts; specifically, the relative increase in respiratory symptom prevalence during winter peaks between seasons was much larger than increases in contacts. Our estimates also suggested that while age played a crucial role in both contact patterns and symptom reporting, the effects of deprivation were less clear and far smaller. Our findings provide insights into changes in behaviours and symptoms during the pandemic, which may help inform future public health policy and infection modelling.

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).

IntroductionThere is limited research on the health outcomes of children who have migrated, or whose parents have migrated, to the UK. MethodsWe used linked birth registration and Census data from the 1991, 2001 and 2011 waves of the Longitudinal Study, covering 1% of the England and Wales population. We derived the prevalence of self-or-caregiver reported limiting long-term illness (2001, 2011 Censuses) and poor health (1991, 2001, 2011 Censuses) among household members <18 years old. We defined immigration background using child and parent country of birth. Logistic regression models assessed the association between immigration background and health outcomes. ResultsThe percentage of children who were first-or second-generation immigrants increased from 16.6% (20120/121109) in 1991 to 24.7% (28965/117116) in 2011. We found no evidence of an association between immigration background and health outcomes in 1991. In 2011, children born outside the UK were less likely to report a limiting long-term illness (odds ratio 0.67; 95% confidence interval 0.58, 0.76) compared to average. Also in 2011, children born in the UK to UK-born parents or non-UK-born fathers/UK-born mothers had higher odds of reporting long-term illness compared to average (1.25; 1.17, 1.32 and 1.21; 1.08, 1.36, respectively). In both 2001 and 2011, children born in the UK to non-UK-born parents had the highest odds of reporting poor health. ConclusionWhilst immigrant children with a first-generation immigrant background are less likely to live with limiting long-term illness, evidence-based National Health Service guidelines for supporting second-generation immigrant children are needed. What is already known on this topicO_LIStudies of adults have identified a healthy migrant effect, where immigrants have lower mortality rates than the host population. C_LIO_LIIt is not clear if this applies to children or to non-mortality outcomes. C_LI What this study addsO_LIThere was no association between childrens immigration background and prevalence of long-term illness before 2011, or poor health before 2001. C_LIO_LIFirst generation immigrant children had lower prevalence of limiting long-term illness, and similar prevalence of poor health to non-immigrant children. C_LIO_LIChildren born in the UK to UK-born parents or second-generation immigrant children via the father had higher prevalence of long-term illness, and UK-born children whose parents were both born abroad had higher prevalence of poor health. C_LI How this study might affect research, practice or policyO_LIThe National Health Service should develop evidence-based guidelines for how health services can support second generation immigrant children. C_LI

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.