Search Results (24)

Cancer disparities in low- and middle-income countries (LMICs) arise from multifaceted interactions between environmental exposures, infectious agents, and systemic inequities, such as limited access to care. The exposome, a framework encompassing the totality of non-genetic exposures throughout life, offers a powerful lens for understanding these disparities. In LMICs, populations are disproportionately affected by air and water pollution, occupational hazards, and oncogenic infections, including human papillomavirus (HPV), hepatitis B virus (HBV), Helicobacter pylori (H. pylori), human immunodeficiency virus (HIV), and neglected tropical diseases, such as schistosomiasis. These infectious agents contribute to increased cancer susceptibility and poor outcomes, particularly in immunocompromised individuals. Moreover, climate change, food insecurity, and barriers to healthcare access exacerbate these risks. This review adopts a population-level exposome approach to explore how environmental and infectious exposures intersect with genetic, epigenetic, and immune mechanisms to influence cancer incidence and progression in LMICs. We highlight the critical pathways linking chronic exposure and inflammation to tumor development and evaluate strategies such as HPV and HBV vaccination, antiretroviral therapy, and environmental regulation. Special attention is given to tools such as exposome-wide association studies (ExWASs), which offer promise for exposure surveillance, early detection, and public health policy. By integrating exposomic insights into national health systems, especially in regions such as sub-Saharan Africa (SSA) and South Asia, LMICs can advance equitable cancer prevention and control strategies. A holistic, exposome-informed strategy is essential for reducing global cancer disparities and improving outcomes in vulnerable populations. Full article

Allergic diseases, particularly respiratory allergies like asthma and allergic rhinitis, are a growing public health concern influenced by environmental factors such as climate change and air pollution. The exposome framework enables a comprehensive assessment of how lifelong environmental exposures shape immune responses and allergic sensitization. Peru’s diverse ecosystems and climates provide a unique setting to investigate regional variations in allergic sensitization. This study characterized these patterns in five Peruvian regions with distinct climatic, urbanization, and socioeconomic characteristics. A total of 268 individuals from Lima, Piura, Tarapoto, Arequipa, and Tacna were analysed for allergen-specific IgE responses using a multiplex IgE detection system. The results revealed significant geographical differences in sensitization frequencies and serodominance profiles, based on descriptive statistics and supported by Chi-square comparative analysis. House dust mites were predominant in humid regions, while Arequipa exhibited higher sensitization to cat allergens. In Tacna, olive pollen showed notable prevalence alongside house dust mites. Tarapoto’s high humidity correlated with increased fungal and cockroach allergen sensitization. Notably, some allergens traditionally considered minor, such as Der p 5 and Der p 21, reached sensitization prevalences close to or exceeding 50% in certain regions. These findings provide the most detailed molecular characterization of allergic sensitization in Peru to date, highlighting the importance of region-specific allergy management strategies. Understanding environmental influences on allergic diseases can support more effective diagnostic, therapeutic, and preventive approaches tailored to diverse geographical contexts. Full article

Ageing is influenced by a complex interplay of genetic, environmental, and lifestyle factors, with increasing evidence highlighting the exposome as a key determinant of healthspan. This review explores the impact of environmental exposures, focusing in particular on pollution, endocrine disruptors, and climate change on the development of age-related diseases such as cardiovascular diseases (CVDs), cancer, and metabolic disorders. Additionally, it examines protective factors that contribute to healthy ageing. A comprehensive literature review was conducted using PubMed, Scopus, and Google Scholar, focusing on studies published between 2000 and 2025. Findings indicate that chronic exposure to pollutants accelerates cellular ageing through mechanisms such as oxidative stress, inflammation, and epigenetic dysregulation. In contrast, longevity hotspots—Blue Zones, Cilento and the mountain villages of Sicily (Sicani and Madonie Mountains)—illustrate how traditional dietary patterns, strong social structures, and reduced environmental toxicity contribute to exceptional health and longevity. Mechanistically, exposome-driven alterations in immune-inflammatory pathways and epigenetic regulation play a central role in modulating ageing trajectories. Understanding these interactions is essential for developing targeted strategies to mitigate harmful exposures and enhance protective factors. This review underscores the urgent need for integrative public health policies that address the environmental determinants of ageing, ultimately promoting a longer and healthier lifespan. Full article

This study investigated the predictive performance of three regression models—Gradient Boosting (GB), Random Forest (RF), and XGBoost—in forecasting mortality due to endocrine, nutritional, and metabolic diseases across Italian provinces. Utilizing a dataset encompassing air pollution metrics and socio-economic indices, the models were trained and tested to evaluate their accuracy and robustness. Performance was assessed using metrics such as coefficient of determination ($r^2$), mean absolute error (MAE), and root mean squared error (RMSE), revealing that GB outperformed both RF and XGB, offering superior predictive accuracy and model stability ($r^2$ = 0.55, MAE = 0.17, and RMSE = 0.05). To further interpret the results, SHAP (SHapley Additive exPlanations) analysis was applied to the best-performing model to identify the most influential features driving mortality predictions. The analysis highlighted the critical roles of specific pollutants, including benzene and socio-economic factors such as life quality and instruction, in influencing mortality rates. These findings underscore the interplay between environmental and socio-economic determinants in health outcomes and provide actionable insights for policymakers aiming to reduce health disparities and mitigate risk factors. By combining advanced machine learning techniques with explainability tools, this research demonstrates the potential for data-driven approaches to inform public health strategies and promote targeted interventions in the context of complex environmental and social determinants of health. Full article

Comorbidities related to cardiovascular disease (CVD) and environmental pollution have emerged as serious concerns. The exposome concept underscores the cumulative impact of environmental factors, including climate change, air pollution, chemicals like PFAS, and heavy metals, on cardiovascular health. Chronic exposure to these pollutants contributes to inflammation, oxidative stress, and endothelial dysfunction, further exacerbating the global burden of CVDs. Specifically, carbon monoxide (CO), ozone, particulate matter (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), heavy metals, pesticides, and micro- and nanoplastics have been implicated in cardiovascular morbidity and mortality through various mechanisms. PM_2.5 exposure leads to inflammation and metabolic disruptions. Ozone and CO exposure induce oxidative stress and vascular dysfunction. NO₂ exposure contributes to cardiac remodeling and acute cardiovascular events, and sulfur dioxide and heavy metals exacerbate oxidative stress and cellular damage. Pesticides and microplastics pose emerging risks linked to inflammation and cardiovascular tissue damage. Monitoring and risk assessment play a crucial role in identifying vulnerable populations and assessing pollutant impacts, considering factors like age, gender, socioeconomic status, and lifestyle disorders. This review explores the impact of cardiovascular disease, discussing risk-assessment methods, intervention strategies, and the challenges clinicians face in addressing pollutant-induced cardiovascular diseases. It calls for stronger regulatory policies, public health interventions, and green urban planning. Full article

Background: Electronic and electrical waste (e-waste) production has emerged to be of global environmental public health concern. E-waste workers, who are frequently exposed to hazardous chemicals through occupational activities, face considerable health risks. Methods: To investigate the metabolic and exposomic changes in these workers, we analyzed whole blood samples from 100 male e-waste workers and 49 controls from the GEOHealth II project (2017–2018 in Accra, Ghana) using LC-MS/MS. A specialized computational workflow was established for exposomics data analysis, incorporating two curated reference libraries for metabolome and exposome profiling. Two feature detection algorithms, asari and centWave, were applied. Results: In comparison to centWave, asari showed better sensitivity in detecting MS features, particularly at trace levels. Principal component analysis demonstrated distinct metabolic profiles between e-waste workers and controls, revealing significant disruptions in key metabolic pathways, including steroid hormone biosynthesis, drug metabolism, bile acid biosynthesis, vitamin metabolism, and prostaglandin biosynthesis. Correlation analyses linked metal exposures to alterations in hundreds to thousands of metabolic features. Functional enrichment analysis highlighted significant perturbations in pathways related to liver function, vitamin metabolism, linoleate metabolism, and dynorphin signaling, with the latter being observed for the first time in e-waste workers. Conclusions: This study provides new insights into the biological impact of prolonged metal exposure in e-waste workers. Full article

Recently, there has been increased scientific and clinical interest in the potential harms associated with ultra-processed foods, including poor mental health, aggression, and antisocial behavior. Research spanning epidemiology, mechanistic pre-clinical work, addiction science, microbiome and exposome science, and human intervention trials has underscored that nutrition is of relevance along the criminal justice continuum. As such, the emerging dietetics research is salient to the thousands of international psychologists and allied mental health professionals that are engaged in justice work, including forensics, prevention, and intervention. In addition, relationships between nutrition and behavior relate to “food crime”, an emergent area unifying criminal justice researchers with psychology, public health, and other interdisciplinary sectors. Food crime scrutinizes the vast harms, including non-communicable diseases and adverse behavioral outcomes, as influenced by the distribution of addictive ultra-processed food products. Here, we examine the emergent research, including biophysiological mechanisms, and evidence indicating that dietary patterns/components intersect with psychosocial vulnerabilities linked with risks of antisocial behavior and justice involvement. Viewed through a prevention lens, the study of nutrition and aggressive behavior should be prioritized, especially if the outcomes emerge as externalities of the global consumption of ultra-processed food. In the context of criminal justice and behavior, there is a need for forensic examination of how industry influence and power structures can undermine matters of food justice. Full article

Currently, exposome studies include a raft of different monitoring tools, including remote sensors, smartphones, omics analyses, distributed lag models, etc. The similarity in structure between the exposome and the microbiota plus their functions led us to pose three pertinent questions from this viewpoint, looking at the actual relationship between the exposome and the microbiota. In terms of the exposome, a bistable equilibrium between health and disease depends on constantly dealing with an ever-changing totality of exposures that together shape an individual from conception to death. Regarding scientific knowledge, the exposome is still lagging in certain areas, like the importance of microorganisms in the equation. The human microbiome is defined as an aggregate assemblage of gut commensals that are hosted by our surfaces related to the external environment. Commensals’ resistance to a variety of environmental exposures, such as antibiotic administration, confirms that a layer of these organisms is protected within the host. The exposome is a conceptual framework defined as the environmental component of the science-inspired systems ideology that shifts from a specificity-based medical approach to reasoning in terms of complexity. A parallel concept in population health research and precision public health is the human flourishing index, which aims to account for the numerous environmental factors that affect individual and population well-being beyond ambient pollution. Full article

Respiratory malignancies, encompassing cancers affecting the lungs, the trachea, and the bronchi, pose a significant and dynamic public health challenge. Given that air pollution stands as a significant contributor to the onset of these ailments, discerning the most detrimental agents becomes imperative for crafting policies aimed at mitigating exposure. This study advocates for the utilization of explainable artificial intelligence (XAI) methodologies, leveraging remote sensing data, to ascertain the primary influencers on the prediction of standard mortality rates (SMRs) attributable to respiratory cancer across Italian provinces, utilizing both environmental and socioeconomic data. By scrutinizing thirteen distinct machine learning algorithms, we endeavor to pinpoint the most accurate model for categorizing Italian provinces as either above or below the national average SMR value for respiratory cancer. Furthermore, employing XAI techniques, we delineate the salient factors crucial in predicting the two classes of SMR. Through our machine learning scrutiny, we illuminate the environmental and socioeconomic factors pertinent to mortality in this disease category, thereby offering a roadmap for prioritizing interventions aimed at mitigating risk factors. Full article

Human flourishing, the state of optimal functioning and well-being across all aspects of an individual’s life, has been a topic of philosophical and theological discussion for centuries. In the mid-20th century, social psychologists and health scientists began exploring the concept of flourishing in the context of health and high-level wellness. However, it is only in recent years, in part due to the USD 43 million Global Flourishing Study including 22 countries, that flourishing has entered the mainstream discourse. Here, we explore this history and the rapid acceleration of research into human flourishing, defined as “the relative attainment of a state in which all aspects of a person’s life are good” by the Harvard University’s Flourishing Program. We also explore the construct of “vitality”, which refers to a sense of aliveness, energy, and motivation; we contend that this has been neglected in the flourishing movement. We explore why incorporating measures of vitality, together with a broader biopsychosocial approach, considers all dimensions of the environment across time (the total exposome), which will greatly advance research, policies, and actions to achieve human flourishing. Full article

The effects of artificial light at night (ALAN) on human health have drawn increased attention in the last two decades. Numerous studies have discussed the effects of ALAN on human health on diverse topics. A broader scope of how ALAN may affect human health is thus urgently needed. This paper depicts a systematic evidence map in a multi-component framework to link ALAN with human health through a comprehensive literature review of English research articles in the past two decades. A three-phase systematic review was conducted after a generalized search of relevant articles from three publication databases, namely Scopus, the Web of Science, and PubMed. In total, 552 research articles were found in four categories and on numerous topics within our framework. We cataloged the evidence that shows direct and indirect as well as positive and negative effects of ALAN on human physical and mental health. We also summarized the studies that consider ALAN as a social determinant of human health. Based on our framework and the systematic evidence map, we also suggest several promising directions for future studies, including method design, co-exposure and exposome studies, and social and environmental justice. Full article

Individuals within genetically diverse populations display broad susceptibility differences upon chemical exposures. Understanding the role of gene-environment interactions (GxE) in differential susceptibility to an expanding exposome is key to protecting public health. However, a chemical’s potential to elicit GxE is often not considered during risk assessment. Previously, we’ve leveraged high-throughput zebrafish (Danio rerio) morphology screening data to reveal patterns of potential GxE effects. Here, using a population genetics framework, we apportioned variation in larval behavior and gene expression in three different PFHxA environments via mixed-effect modeling to assess significance of GxE term. We estimated the intraclass correlation (ICC) between full siblings from different families using one-way random-effects model. We found a significant GxE effect upon PFHxA exposure in larval behavior, and the ICC of behavioral responses in the PFHxA exposed population at the lower concentration was 43.7%, while that of the control population was 14.6%. Considering global gene expression data, a total of 3746 genes showed statistically significant GxE. By showing evidence that heritable genetics are directly affecting gene expression and behavioral susceptibility of individuals to PFHxA exposure, we demonstrate how standing genetic variation in a heterogeneous population such as ours can be leveraged to test for potential GxE. Full article

Chemical exposures from diverse sources merge on a limited number of molecular pathways described as toxicity pathways. Changes in the same set of molecular pathways in different cell and tissue types may generate seemingly unrelated health conditions. Today, no approaches are available to predict in an unbiased way sensitivities of different disease states and their combinations to multi-chemical exposures across the exposome. We propose an inductive in-silico workflow where sensitivities of genes to chemical exposures are identified based on the overlap of existing genomic datasets, and data on sensitivities of individual genes is further used to sequentially derive predictions on sensitivities of molecular pathways, disease states, and groups of disease states (syndromes). Our analysis predicts that conditions representing the most significant public health problems are among the most sensitive to cumulative chemical exposures. These conditions include six leading types of cancer in the world (prostatic, breast, stomach, lung, colorectal neoplasms, and hepatocellular carcinoma), obesity, type 2 diabetes, non-alcoholic fatty liver disease, autistic disorder, Alzheimer’s disease, hypertension, heart failure, brain and myocardial ischemia, and myocardial infarction. Overall, our predictions suggest that environmental risk factors may be underestimated for the most significant public health problems. Full article

Columbus, Ohio is one of the more prosperous, well-educated, and progressive cities in the United States. However, it ranks as the second worst life expectancy at birth, has a census tract wealth gap (27-year disparity), and one of the higher infant mortality rates in the country. These data suggest that there are likely several high-risk, vulnerable neighborhoods in Columbus with residents experiencing disparate and adverse outcomes. Illustrative of this fact are studies that have examined the social processes and mechanisms through which neighborhood contexts are at the forefront, including exposures to chemical stressors such as particulate matter (PM_2.5) as well as non-chemical stressors including violence, social determinants of health, zoning, and land use policies. It is documented that disparate and adverse outcomes are magnified in the vulnerable neighborhoods on the Near East Side as compared to Columbus city proper, Franklin County and/or the state of Ohio. As such, we developed a nuanced community engagement framework to identify potential environmental hazards associated with adverse pregnancy outcomes in those census tracts. The refined framework uses a blended version of traditional community-based participatory research (CBPR) models and is referred to as E⁶, Enhancing Environmental Endeavors via e-Equity, Education, and Empowerment. Full article

Validated physical activity (PA) questionnaires are crucial for collecting information in large epidemiological studies during childhood. Thus, this study analyzed the validity of a parent-reported PA questionnaire based on the Children’s Leisure Activities Study Survey by accelerometry in European children aged from 6 to 12 years old. We used data from 230 children of the Human Early-Life Exposome and Infancia y Medio Ambiente projects. Mean differences between moderate-to-vigorous PA (MVPA) reported by the questionnaire and the accelerometer were calculated (min/day), and its associated factors were explored by multiple robust linear regression. The agreement between methods was examined using a Bland–Altman plot. The concurrent validity of assessing MVPA was analyzed by cohort-adjusted Spearman’s partial correlations. ROC curve analysis was also used to explore the questionnaire’s capability to identify active children based on the World Health Organization guidelines. A moderate correlation was found between parent-reported and accelerometer MVPA (rho = 0.41, p < 0.001). The child’s sex (girl) was statistically associated with the mean MVPA difference between methods. However, this questionnaire accurately identified physically active children (area under the curve = 83.8% and 82.7% for boys and girls, cut-points = 68.6 and 45.4 min/day in MVPA, respectively). Consequently, this questionnaire is suitable for classifying active children in order to monitor public health interventions regarding PA. Full article