Summary Cancer is a global and growing, but not uniform, problem. An increasing proportion of the burden is falling on low-income and middle-income countries because of not only demographic change ...but also a transition in risk factors, whereby the consequences of the globalisation of economies and behaviours are adding to an existing burden of cancers of infectious origin. We argue that primary prevention is a particularly effective way to fight cancer, with between a third and a half of cancers being preventable on the basis of present knowledge of risk factors. Primary prevention has several advantages: the effectiveness could have benefits for people other than those directly targeted, avoidance of exposure to carcinogenic agents is likely to prevent other non-communicable diseases, and the cause could be removed or reduced in the long term—eg, through regulatory measures against occupational or environmental exposures (ie, the preventive effort does not need to be renewed with every generation, which is especially important when resources are in short supply). Primary prevention must therefore be prioritised as an integral part of global cancer control.
The understanding of disease etiology and pathogenesis has radically changed as a consequence of the new challenges posed by climate change, environmental degradation and emerging infectious ...diseases. The awareness of the influence of distal causes (e.g. planetary changes at the roots of new pandemics), of the social environment and of early life exposures calls for innovative models of disease onset. Here we propose a scheme for the practice of epidemiology and toxicology that incorporates new recent advancements in both disciplines, under the general umbrella of the “exposome”. The exposome approach to disease encompasses a lifecourse perspective from conception onwards, and the investigation of the role played by all exposures individuals undergo in their lives. These include social inequalities and psychosocial influences, in addition to chemical, biological and physical exposures. We stress the role played by social differences and inequalities in the course of life as an overarching factor that influences downstream layers (including behaviours). We show that the idea of “lifecourse exposome” is compatible with the current interpretation of Adverse Outcome Pathways in toxicology, and in fact we propose an extension of the concept towards “lifecourse Adverse Outcome Pathways”. We propose to merge different research perspectives and promote an encounter between the sociological perspective of “biography” (using Pierre Bourdieu’s conceptual framework) and biology, according to the idea of accumulated biological capital of individuals. We also propose to treat social capital (including inequalities) no longer as a confounding factor but as an overarching determinant, perhaps the most important of all because it is the one that influences all other exposures downstream. The importance of early exposures in a lifecourse perspective leads to policy implications, i.e. investing more in the various forms of capital (social, economic, cultural) in early life.
The impact of the COVID-19 pandemic on excess mortality from all causes in 2020 varied across and within European countries. Using data for 2015-2019, we applied Bayesian spatio-temporal models to ...quantify the expected weekly deaths at the regional level had the pandemic not occurred in England, Greece, Italy, Spain, and Switzerland. With around 30%, Madrid, Castile-La Mancha, Castile-Leon (Spain) and Lombardia (Italy) were the regions with the highest excess mortality. In England, Greece and Switzerland, the regions most affected were Outer London and the West Midlands (England), Eastern, Western and Central Macedonia (Greece), and Ticino (Switzerland), with 15-20% excess mortality in 2020. Our study highlights the importance of the large transportation hubs for establishing community transmission in the first stages of the pandemic. Here, we show that acting promptly to limit transmission around these hubs is essential to prevent spread to other regions and countries.
What is new in the exposome? Vineis, Paolo; Robinson, Oliver; Chadeau-Hyam, Marc ...
Environment international,
October 2020, 2020-10-00, 2020-10-01, Volume:
143
Journal Article
Peer reviewed
Open access
The exposome concept refers to the totality of exposures from a variety of external and internal sources including chemical agents, biological agents, or radiation, from conception onward, over a ...complete lifetime. It encompasses also “psychosocial components” including the impact of social relations and socio-economic position on health. In this review we provide examples of recent contributions from exposome research, where we believe their application will be of the greatest value for moving forward. So far, environmental epidemiology has mainly focused on hard outcomes, such as mortality, disease exacerbation and hospitalizations. However, there are many subtle outcomes that can be related to environmental exposures, and investigations can be facilitated by an improved understanding of internal biomarkers of exposure and response, through the application of omic technologies. Second, though we have a wealth of studies on environmental pollutants, the assessment of causality is often difficult because of confounding, reverse causation and other uncertainties. Biomarkers and omic technologies may allow better causal attribution, for example using instrumental variables in triangulation, as we discuss here. Even more complex is the understanding of how social relationships (in particular socio-economic differences) influence health and imprint on the fundamental biology of the individual. The identification of molecular changes that are intermediate between social determinants and disease status is a way to fill the gap. Another field in which biomarkers and omics are relevant is the study of mixtures. Epidemiology often deals with complex mixtures (e.g. ambient air pollution, food, smoking) without fully disentangling the compositional complexity of the mixture, or with rudimentary approaches to reflect the overall effect of multiple exposures or components.
From the point of view of disease mechanisms, most models hypothesize that several stages need to be transitioned through health to the induction of disease, but very little is known about the characteristics and temporal sequence of such stages. Exposome models reinforce the idea of a biography-to-biology transition, in that everyone’s disease is the product of the individual history of exposures, superimposed on their underlying genetic susceptibilities. Finally, exposome research is facilitated by technological developments that complement traditional epidemiological study designs. We describe in depth one such new tools, adductomics. In general, the development of high-resolution and high-throughput technologies interrogating multiple -omics (such as epigenomics, transcriptomics, proteomics, adductomics and metabolomics) yields an unprecedented perspective into the impact of the environment in its widest sense on disease.
The world of the exposome is rapidly evolving, though a huge gap still needs to be filled between the original expectations and the concrete achievements. Perhaps the most urgent need is for the establishment of a new generation of cohort studies with appropriately specified biosample collection, improved questionnaire data (including social variables), and the deployment of novel technologies that allow better characterization of individual environmental exposures, ranging from personal monitoring to satellite based observations.
Unhealthy behaviors and their social patterning have been frequently proposed as factors mediating socioeconomic differences in health. However, a clear quantification of the contribution of health ...behaviors to the socioeconomic gradient in health is lacking. This study systematically reviews the role of health behaviors in explaining socioeconomic inequalities in health.
Published studies were identified by a systematic review of PubMed, Embase and Web-of-Science. Four health behaviors were considered: smoking, alcohol consumption, physical activity and diet. We restricted health outcomes to cardiometabolic disorders and mortality. To allow comparison between studies, the contribution of health behaviors, or the part of the socioeconomic gradient in health that is explained by health behaviors, was recalculated in all studies according to the absolute scale difference method.
We identified 114 articles on socioeconomic position, health behaviors and cardiometabolic disorders or mortality from electronic databases and articles reference lists. Lower socioeconomic position was associated with an increased risk of all-cause mortality and cardiometabolic disorders, this gradient was explained by health behaviors to varying degrees (minimum contribution −43%; maximum contribution 261%).
Health behaviors explained a larger proportion of the SEP-health gradient in studies conducted in North America and Northern Europe, in studies examining all-cause mortality and cardiovascular disease, among men, in younger individuals, and in longitudinal studies, when compared to other settings. Of the four behaviors examined, smoking contributed the most to social inequalities in health, with a median contribution of 19%.
Health behaviors contribute to the socioeconomic gradient in cardiometabolic disease and mortality, but this contribution varies according to population and study characteristics. Nevertheless, our results should encourage the implementation of interventions targeting health behaviors, as they may reduce socioeconomic inequalities in health and increase population health.
•Health behaviors are key contributors to the socioeconomic gradient in health.•Multiple health behaviors contribute more than individual health behaviors.•Smoking contributes more than alcohol, physical activity, or dietary patterns.•The contribution of health behaviors varies according to multiple factors.
Abstract
The aging process is characterized by the presence of high interindividual variation between individuals of the same chronical age prompting a search for biomarkers that capture this ...heterogeneity. Epigenetic clocks measure changes in DNA methylation levels at specific CpG sites that are highly correlated with calendar age. The discrepancy resulting from the regression of DNA methylation age on calendar age is hypothesized to represent a measure of biological aging with a positive/negative residual signifying age acceleration (AA)/deceleration, respectively. The present study examines the associations of 4 epigenetic clocks—Horvath, Hannum, PhenoAge, GrimAge—with a wide range of clinical phenotypes (walking speed, grip strength, Fried frailty, polypharmacy, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MOCA), Sustained Attention Reaction Time, 2-choice reaction time), and with all-cause mortality at up to 10-year follow-up, in a sample of 490 participants in the Irish Longitudinal Study on Ageing (TILDA). HorvathAA and HannumAA were not predictive of health; PhenoAgeAA was associated with 4/9 outcomes (walking speed, frailty MOCA, MMSE) in minimally adjusted models, but not when adjusted for other social and lifestyle factors. GrimAgeAA by contrast was associated with 8/9 outcomes (all except grip strength) in minimally adjusted models, and remained a significant predictor of walking speed, .polypharmacy, frailty, and mortality in fully adjusted models. Results indicate that the GrimAge clock represents a step-improvement in the predictive utility of the epigenetic clocks for identifying age-related decline in an array of clinical phenotypes promising to advance precision medicine.
Here I compare two types of evidence that have recently emerged from the literature. This Commentary is a contribution to the Frontiers Research Topic on social disparities in aging, and aims to draw ...attention to the novel connections that link social disparities, the biological capital of individuals, and policy strategies. The biological capital (as defined in the paper), accrued since conception by individuals, in turn affects their social, cultural, and economic capitals, and thus creates a positive feedback loop. In a large network funded by the European Commission, Lifepath, we have shown that the determinants of health inequalities start in early life and cumulate throughout the life-course. For example, exposure to adverse childhood experiences (ACEs) influences the likelihood of later in life health effects, including poor aging. In this paper I compare two types of evidence that have recently emerged from the literature. One addresses the role of early vs. late exposures to risk factors for aging and mortality, including ACEs, using e.g., microsimulation models. The second type of evidence, provided in a recent document of the WHO European Regional Office, is based on the analysis of five broad determinants of health inequalities and eight different macroeconomic policies to tackle such inequalities. Six of the policies, if enacted, have the potential to reduce inequalities in the short term by increasing public expenditure on housing and community amenities, increasing expenditure on labor market policies, reducing income inequality, increasing social protection expenditure, reducing unemployment, and/or reducing out-of-pocket payments for health. Both of these lines of evidence suggest that there are ample opportunities for policy interventions. I also discuss the need for analytical methods to bridge the two types of analyses (biomedical and macroeconomic), i.e., fill the gap between analyses based on individual determinants of health inequalities and those based on societal determinants, to help create more effective policy-making. Also, I propose that before launching large projects to reduce health inequalities, well-designed experiments must be conducted to test their efficacy. These experiments, though, are challenging when addressing social policies, in consideration of ethical constraints and timescales.
Particulate matter (PM) in outdoor air pollution was recently designated a Group I carcinogen by the International Agency for Research on Cancer (IARC). This determination was based on the evidence ...regarding the relationship of PM2.5 and PM10 to lung cancer risk; however, the IARC evaluation did not include a quantitative summary of the evidence.
Our goal was to provide a systematic review and quantitative summary of the evidence regarding the relationship between PM and lung cancer.
We conducted meta-analyses of studies examining the relationship of exposure to PM2.5 and PM10 with lung cancer incidence and mortality. In total, 18 studies met our inclusion criteria and provided the information necessary to estimate the change in lung cancer risk per 10-μg/m3 increase in exposure to PM. We used random-effects analyses to allow between-study variability to contribute to meta-estimates.
The meta-relative risk for lung cancer associated with PM2.5 was 1.09 (95% CI: 1.04, 1.14). The meta-relative risk of lung cancer associated with PM10 was similar, but less precise: 1.08 (95% CI: 1.00, 1.17). Estimates were robust to restriction to studies that considered potential confounders, as well as subanalyses by exposure assessment method. Analyses by smoking status showed that lung cancer risk associated with PM2.5 was greatest for former smokers 1.44 (95% CI: 1.04, 1.22), followed by never-smokers 1.18 (95% CI: 1.00, 1.39), and then current smokers 1.06 (95% CI: 0.97, 1.15). In addition, meta-estimates for adenocarcinoma associated with PM2.5 and PM10 were 1.40 (95% CI: 1.07, 1.83) and 1.29 (95% CI: 1.02, 1.63), respectively.
The results of these analyses, and the decision of the IARC Working Group to classify PM and outdoor air pollution as carcinogenic (Group 1), further justify efforts to reduce exposures to air pollutants that can arise from many sources.
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