Explore the vast range of titles available.

Assessing the burden of COVID-19 on the basis of medically attended case numbers is suboptimal given its reliance on testing strategy, changing case definitions, and disease presentation. Population-based serosurveys measuring anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) antibodies provide one method for estimating infection rates and monitoring the progression of the epidemic. Here, we estimate weekly seroprevalence of anti-SARS-CoV-2 antibodies in the population of Geneva, Switzerland, during the epidemic. The SEROCoV-POP study is a population-based study of former participants of the Bus Santé study and their household members. We planned a series of 12 consecutive weekly serosurveys among randomly selected participants from a previous population-representative survey, and their household members aged 5 years and older. We tested each participant for anti-SARS-CoV-2-IgG antibodies using a commercially available ELISA. We estimated seroprevalence using a Bayesian logistic regression model taking into account test performance and adjusting for the age and sex of Geneva's population. Here we present results from the first 5 weeks of the study. Between April 6 and May 9, 2020, we enrolled 2766 participants from 1339 households, with a demographic distribution similar to that of the canton of Geneva. In the first week, we estimated a seroprevalence of 4·8% (95% CI 2·4–8·0, n=341). The estimate increased to 8·5% (5·9–11·4, n=469) in the second week, to 10·9% (7·9–14·4, n=577) in the third week, 6·6% (4·3–9·4, n=604) in the fourth week, and 10·8% (8·2–13·9, n=775) in the fifth week. Individuals aged 5–9 years (relative risk [RR] 0·32 [95% CI 0·11–0·63]) and those older than 65 years (RR 0·50 [0·28–0·78]) had a significantly lower risk of being seropositive than those aged 20–49 years. After accounting for the time to seroconversion, we estimated that for every reported confirmed case, there were 11·6 infections in the community. These results suggest that most of the population of Geneva remained uninfected during this wave of the pandemic, despite the high prevalence of COVID-19 in the region (5000 reported clinical cases over <2·5 months in the population of half a million people). Assuming that the presence of IgG antibodies is associated with immunity, these results highlight that the epidemic is far from coming to an end by means of fewer susceptible people in the population. Further, a significantly lower seroprevalence was observed for children aged 5–9 years and adults older than 65 years, compared with those aged 10–64 years. These results will inform countries considering the easing of restrictions aimed at curbing transmission. Swiss Federal Office of Public Health, Swiss School of Public Health (Corona Immunitas research program), Fondation de Bienfaisance du Groupe Pictet, Fondation Ancrage, Fondation Privée des Hôpitaux Universitaires de Genève, and Center for Emerging Viral Diseases.

Chronic inflammation has been proposed as having a prominent role in the construction of social inequalities in health. Disentangling the effects of early life and adulthood social disadvantage on inflammation is key in elucidating biological mechanisms underlying socioeconomic disparities. Here we explore the relationship between socioeconomic position (SEP) across the life course and inflammation (as measured by CRP levels) in up to 23,008 participants from six European cohort studies from three countries conducted between 1958 and 2013. We find a consistent inverse association between SEP and CRP across cohorts, where participants with a less advantaged SEP have higher levels of inflammation. Educational attainment is most strongly related to inflammation, after adjusting for health behaviours, body mass index and later-in-life SEP. These findings suggest socioeconomic disadvantage in young adulthood is independently associated with later life inflammation calling for further studies of the pathways operating through educational processes. Here, the authors explore the relationship between socioeconomic position (SEP) across the life course and inflammation in a multi-cohort study and show that educational attainment is most strongly related to inflammation, suggesting that socioeconomic disadvantage in young adulthood is independently associated with later life inflammation.

(1) Background: Socioeconomic conditions and environmental exposures are well-established determinants of health and aging, yet the pathways through which they influence the aging process remain insufficiently understood. Clarifying these mechanisms is critical for developing effective, equity-focused public health interventions to support healthy aging; (2) Methods: We conducted a narrative review examining the relationships between socioeconomic conditions, environmental exposures, and aging-related health outcomes. While the scope was intentionally broad to capture diverse exposures and outcomes, we applied a systematic search strategy to identify relevant peer-reviewed studies; (3) Results: The search populated over 4000 articles; 33 relevant papers were selected. The evidence suggests that environmental exposures may mediate or modify the effects of socioeconomic disadvantage on aging. Conversely, socioeconomic conditions can alter the association between environmental factors and aging outcomes. Disadvantaged populations consistently face higher environmental burdens and exhibit poorer aging outcomes, including accelerated biological aging and increased risk of age-related disease; (4) Conclusions: The complex interplay between social and environmental factors contributes to disparities in aging. Our integrative approach highlights the need for more intersectional, longitudinal research to inform interventions that address the social and environmental determinants of healthy aging.

Background Sport participation is an important component of a healthy lifestyle and is known to be more common among privileged individuals. However, few studies 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. Methods We used 2005–2019 data from the Bus Santé 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). Results Out of 7769 participants (50.8% 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) for football and 4.25 (95%CI: 2.68–6.75) for tennis/badminton for education. Yearly absolute inequalities in sport participation tended to increase between 2005 and 2019 for household income, especially among women and older adults. Conclusions We observed strong socio-economic inequalities in sport participation in Geneva, with different magnitude depending on the sport type. 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.

The Covid-19 pandemic—and its social and economic fallout—has thrust social and health-related inequalities into the spotlight. The pandemic, and our response to it, has induced new inequalities both within and between nations. However, now that highly efficacious vaccines are available, one might reasonably presume that we have in our hands the tools to address pandemic-associated inequalities. Nevertheless, two prominent social science theories, fundamental cause theory and diffusion of innovation theory suggest otherwise. Together, these theories predict that better resourced individuals and countries will jockey to harness the greatest vaccine benefit for themselves, leaving large populations of disadvantaged people unprotected. While many other life-saving prevention measures have been distributed unequally in ways these theories would predict, the COVID-19 vaccines represent a different kind of case. As the disease is so highly infectious and because mutations lead to new variants so rapidly, any inequality-generating process that leaves disadvantaged individuals and countries behind acts to put everyone—rich and poor—at risk. It is time that we ensure the equitable distribution of this life-saving benefit. As the fundamental cause and diffusion of innovation theories help illuminate processes that regularly produce inequities, we turn to them to reason about the rollout of the COVID-19 vaccines. Specifically, employ them to suggest countermoves that may be necessary to avoid an irrational and inequitable vaccine rollout that ends up unfavorably affecting all people.

We examined the determinants of adolescents' Health-Related Quality of Life (HRQoL) and psychological distress (self-reported and parent-reported) during the COVID-19 pandemic, using a random sample of the population of Geneva, Switzerland. Data was drawn from participants aged 14-17 years, who participated with their families to a serosurvey conducted in November and December 2020. Adolescents' HRQoL was evaluated using the validated adolescent-reported KIDSCREEN-10 and parent-reported KINDL.sup.® scales. Psychological distress was assessed with self-reported sadness and loneliness, and using the KINDL.sup.® emotional well-being scale. Using generalized estimating equations, we examined the role of socio-demographic, family and behavioural characteristics in influencing adolescents' mental health status and wellbeing. Among 240 adolescents, 11% had a low HRQoL, 35% reported sadness and 23% reported loneliness. Based on parents' perception, 12% of the adolescents had a low HRQoL and 16% a low emotional well-being. Being a girl (aOR = 3.20; 95%CI: 1.67-6.16), increased time on social media (aOR = 2.07; 95%CI: 1.08-3.97), parents' average to poor mood (aOR = 2.62; 95%CI: 1.10-6.23) and average to poor household financial situation (aOR = 2.31; IC95%: 1.01-6.10) were associated with an increased risk of sadness. Mismatches between adolescents' and their parents' perception of HRQoL were more likely for girls (aOR = 2.88; 95%CI: 1.54-5.41) and in households with lower family well-being (aOR = 0.91; 95%CI: 0.86-0.96). A meaningful proportion of adolescents experienced low well-being during the second wave of COVID-19, and average well-being was lower than pre-pandemic estimates. Adolescents living in underprivileged or distressed families seemed particularly affected. Monitoring is necessary to evaluate the long-term effects of the pandemic on adolescents.

Cardiovascular diseases (CVD) mortality has been shown to follow a seasonal pattern. Several studies suggested several possible determinants of this pattern, including misclassification of causes of deaths. We aimed at assessing seasonality in overall, CVD, cancer and non-CVD/non-cancer mortality using data from 19 countries from different latitudes. Monthly mortality data were compiled from 19 countries, amounting to over 54 million deaths. We calculated ratios of the observed to the expected numbers of deaths in the absence of a seasonal pattern. Seasonal variation (peak to nadir difference) for overall and cause-specific (CVD, cancer or non-CVD/non-cancer) mortality was analyzed using the cosinor function model. Mortality from overall, CVD and non-CVD/non-cancer showed a consistent seasonal pattern. In both hemispheres, the number of deaths was higher than expected in winter. In countries close to the Equator the seasonal pattern was considerably lower for mortality from any cause. For CVD mortality, the peak to nadir differences ranged from 0.185 to 0.466 in the Northern Hemisphere, from 0.087 to 0.108 near the Equator, and from 0.219 to 0.409 in the Southern Hemisphere. For cancer mortality, the seasonal variation was nonexistent in most countries. In countries with seasonal variation, mortality from overall, CVD and non-CVD/non-cancer show a seasonal pattern with mortality being higher in winter than in summer. Conversely, cancer mortality shows no substantial seasonality.

Differences in morbidity and mortality between socioeconomic groups constitute one of the most consistent findings of epidemiologic research. However, research on social inequalities in health has yet to provide a comprehensive understanding of the mechanisms underlying this association. In recent analysis, we showed health behaviours, assessed longitudinally over the follow-up, to explain a major proportion of the association of socioeconomic status (SES) with mortality in the British Whitehall II study. However, whether health behaviours are equally important mediators of the SES-mortality association in different cultural settings remains unknown. In the present paper, we examine this issue in Whitehall II and another prospective European cohort, the French GAZEL study. We included 9,771 participants from the Whitehall II study and 17,760 from the GAZEL study. Over the follow-up (mean 19.5 y in Whitehall II and 16.5 y in GAZEL), health behaviours (smoking, alcohol consumption, diet, and physical activity), were assessed longitudinally. Occupation (in the main analysis), education, and income (supplementary analysis) were the markers of SES. The socioeconomic gradient in smoking was greater (p<0.001) in Whitehall II (odds ratio [OR] = 3.68, 95% confidence interval [CI] 3.11-4.36) than in GAZEL (OR = 1.33, 95% CI 1.18-1.49); this was also true for unhealthy diet (OR = 7.42, 95% CI 5.19-10.60 in Whitehall II and OR = 1.31, 95% CI 1.15-1.49 in GAZEL, p<0.001). Socioeconomic differences in mortality were similar in the two cohorts, a hazard ratio of 1.62 (95% CI 1.28-2.05) in Whitehall II and 1.94 in GAZEL (95% CI 1.58-2.39) for lowest versus highest occupational position. Health behaviours attenuated the association of SES with mortality by 75% (95% CI 44%-149%) in Whitehall II but only by 19% (95% CI 13%-29%) in GAZEL. Analysis using education and income yielded similar results. Health behaviours were strong predictors of mortality in both cohorts but their association with SES was remarkably different. Thus, health behaviours are likely to be major contributors of socioeconomic differences in health only in contexts with a marked social characterisation of health behaviours. Please see later in the article for the Editors' Summary.

Socioeconomic adversity in early life has been hypothesized to \"program\" a vulnerable phenotype with exaggerated inflammatory responses, so increasing the risk of developing type 2 diabetes in adulthood. The aim of this study is to test this hypothesis by assessing the extent to which the association between lifecourse socioeconomic status and type 2 diabetes incidence is explained by chronic inflammation. We use data from the British Whitehall II study, a prospective occupational cohort of adults established in 1985. The inflammatory markers C-reactive protein and interleukin-6 were measured repeatedly and type 2 diabetes incidence (new cases) was monitored over an 18-year follow-up (from 1991-1993 until 2007-2009). Our analytical sample consisted of 6,387 non-diabetic participants (1,818 women), of whom 731 (207 women) developed type 2 diabetes over the follow-up. Cumulative exposure to low socioeconomic status from childhood to middle age was associated with an increased risk of developing type 2 diabetes in adulthood (hazard ratio [HR] = 1.96, 95% confidence interval: 1.48-2.58 for low cumulative lifecourse socioeconomic score and HR = 1.55, 95% confidence interval: 1.26-1.91 for low-low socioeconomic trajectory). 25% of the excess risk associated with cumulative socioeconomic adversity across the lifecourse and 32% of the excess risk associated with low-low socioeconomic trajectory was attributable to chronically elevated inflammation (95% confidence intervals 16%-58%). In the present study, chronic inflammation explained a substantial part of the association between lifecourse socioeconomic disadvantage and type 2 diabetes. Further studies should be performed to confirm these findings in population-based samples, as the Whitehall II cohort is not representative of the general population, and to examine the extent to which social inequalities attributable to chronic inflammation are reversible.

Though Switzerland has one of the highest life expectancies in the world, this global indicator may mask significant disparities at a local level. The present study used a spatial cluster detection approach based on individual death records to investigate the geographical footprint of life expectancy inequalities in the state of Geneva, Switzerland. Individual-level mortality data (n = 22,751) were obtained from Geneva’s official death notices (2009–2016). We measured life expectancy inequalities using the years of potential life lost or gained (YPLLG) metric, defined as the difference between an individual’s age at death and their life expectancy at birth. We assessed the spatial dependence of YPLLG across the state of Geneva using spatial autocorrelation statistics (Local Moran’s I). To ensure the robustness of the patterns discovered, we ran the analyses for ten random subsets of 10,000 individuals taken from the 22,751 deceased. We also repeated the spatial analysis for YPLLG before and after controlling for individual-level and neighborhood-level covariates. The results showed that YPLLG was not randomly distributed across the state of Geneva. The ten random subsets revealed no significant difference with the geographic footprint of YPLLG and the population characteristics within Local Moran cluster types, suggesting robustness for the observed spatial structure. The proportion of women, the proportion of Swiss, the neighborhood median income, and the neighborhood median age were all significantly lower for populations in low YPLLG clusters when compared to populations in high YPLLG clusters. After controlling for individual-level and neighborhood-level covariates, we observed a reduction of 43% and 39% in the size of low and high YPLLG clusters, respectively. To our knowledge, this is the first study in Switzerland using spatial cluster detection methods to investigate inequalities in life expectancy at a local scale and based on individual data. We identified clear geographic footprints of YPLLG, which may support further investigations and guide future public health interventions at the local level.