A place to start?

How do economic geographers determine where to begin their research projects, where to locate and delimit their case studies, where and how to "cut in" to problems? In the absence of self-evident or pregiven answers to these questions, the problem-cum-choice of where and how to start is inescapably tangled up with issues of preliminary conceptualization and indeed theorization, since cases are not so much found as made, being in various ways coproduced with different "theory-method packages." There is (and can be) no singular or universal answer to these questions. Instead, this brief intervention outlines one rationale for getting "started," founded as such rationales should be with reference a particular approach or mode of theorization. The approach here centers on the problematic of recombinant development, on the role of extended case-study designs, and on the still sparsely realized potential of conjunctural modes of analysis.

Applying a Bayesian Spatiotemporal Model to Examine Excess County-Level Cardiovascular Disease Death Rates During the COVID-19 Pandemic.

Amid the COVID-19 pandemic, national cardiovascular disease (CVD) death rates increased, especially among younger adults. County-level variation has not been documented. Using county-level CVD deaths (ICD-10 codes: I00-I99) from the US National Vital Statistics System, we developed a Bayesian multivariate spatiotemporal model to estimate excess CVD death rates in 2020 based on trends from 2010-2019 for adults aged 35-64 and ≥65 years. Among adults aged 35-64 years, 64.7% of counties experienced significant excess CVD death rates. The median county-level CVD death rate in 2020 was 150 per 100,000 persons, which exceeded the predicted rate for 2020 (median excess death rate: 11 per 100,000; median excess rate ratio: 1.08). Among adults aged ≥65 years, 15.2% of counties experienced significant excess CVD death rates. The median county-level CVD death rate was 1,546 per 100,000 in 2020, which exceeded the predicted rate in 2020 (median excess death rate: 48 per 100,000, median excess rate ratio: 1.03). Counties with significant excess death rates in 2020 were geographically dispersed. In 2020, disruptions of county-level CVD death rates were widespread, especially among younger adults, suggesting the continued importance of CVD prevention and treatment in younger adults in communities across the country.

Causal discovery reveals complex patterns of drought-induced displacement.

The increasing frequency and severity of droughts present a significant risk to vulnerable regions of the globe, potentially leading to substantial human displacement in extreme situations. Drought-induced displacement is a complex and multifaceted issue that can perpetuate cycles of poverty, exacerbate food and water scarcity, and reinforce socio-economic inequalities. However, our understanding of human mobility in drought scenarios is currently limited, inhibiting accurate predictions and effective policy responses. Drought-induced displacement is driven by numerous factors and identifying its key drivers, causal-effect lags, and consequential effects is often challenging, typically relying on mechanistic models and qualitative assumptions. This paper presents a novel, data-driven methodology, grounded in causal discovery, to retrieve the drivers of drought-induced displacement within Somalia from 2016 to 2023. Our model exposes the intertwined vulnerabilities and the leading times that connect drought impacts, water and food security systems along with episodes of violent conflict, emphasizing that causal mechanisms change across districts. These findings pave the way for the development of algorithms with the ability to learn from human mobility data, enhancing anticipatory action, policy formulation, and humanitarian aid.

Combining short- and long-read sequencing unveils geographically structured diversity in Borrelia miyamotoi.

Borrelia miyamotoi is an emerging Ixodes tick-borne human pathogen in the Northern hemisphere. The aim of the current study was to compare whole genome sequences of B. miyamotoi isolates from different continents. Using a combination of Illumina and PacBio platforms and a novel genome assembly and plasmid typing pipeline, we reveal that the 21 sequenced B. miyamotoi isolates and publically available B. miyamotoi genomes from North America, Asia, and Europe form genetically distinct populations and cluster according to their geographical origin, where distinct Ixodes species are endemic. We identified 20 linear and 17 circular plasmid types and the presence of specific plasmids for isolates originating from different continents. Linear plasmids lp12, lp23, lp41, and lp72 were core plasmids found in all isolates, with lp41 consistently containing the vmp expression site. Our data provide insights into the genetic basis of vector competence, virulence, and pathogenesis of B. miyamotoi.

Deep transformer-based heterogeneous spatiotemporal graph learning for geographical traffic forecasting.

Accurate geographical traffic forecasting plays a critical role in urban transportation planning, traffic management, and geospatial artificial intelligence (GeoAI). Although deep learning models have made significant progress in geographical traffic forecasting, they still face challenges in effectively capturing long-term temporal dependencies and modeling heterogeneous dynamic spatial dependencies. To address these issues, we propose a novel deep transformer-based heterogeneous spatiotemporal graph learning model for geographical traffic forecasting. Our model incorporates a temporal transformer that captures long-term temporal patterns in traffic data without simple data fusion. Furthermore, we introduce adaptive normalized graph structures within different graph layers, enabling the model to capture dynamic spatial dependencies and adapt to diverse traffic scenarios, especially for the heterogeneous relationship. We conduct comprehensive experiments and visualization on four primary public datasets and demonstrate that our model achieves state-of-the-art results in comparison to existing methods.

From across the globe - traumatic injuries are an international concern at the US-Mexico border wall.

Introduction: Socio-economic and political events of recent years have caused a significant increase in immigrants attempting to illegally cross the United States (US)-Mexico border. While a 30-foot border wall separates the US and Mexico, immigrants from around the world have used this location as their point of entry to the US. These border crossings have led to a dramatic increase in major trauma resulting in increased inpatient resource utilization and the need for comprehensive hospital services. The aim of this study was to describe the nationality of injured immigrants admitted to a Trauma Center serving a segment of the US-Mexico border wall and to report their ultimate destinations after discharge. Methods: We performed a retrospective review of patients admitted to an academic, Level 1 Trauma Center after injury at the US-Mexico border wall from 2021 to 2022. Demographic information was obtained from the trauma registry. The electronic medical record was searched to identify each patient's self-reported country of origin. Patients' nationality was then stratified by region of the world to understand geographic representation of border injury admissions. Results: We identified 597 patients injured while crossing the US-Mexico border wall representing 38 different countries. The mean age of patients was 32.2±10.4 years and 446 (75%) were male. Most patients (405, 67.8%) were Mexican, followed by 23 (3.9%) patients from Peru, 17 (2.8%) patients from India, 14 (2.3%) patients from El Salvador, 13 (2.2%) patients from Cuba and 12 (2.0%) patients from Jamaica. When considering regions of the world other than Mexico, patients were most commonly from Africa, South America and Central America. Conclusion: The increased volume of trauma associated with the US-Mexico border wall is a humanitarian and health crisis.(1) The diverse national origin of patients admitted after injury from border wall falls has shed new light on the social and interpreter services needed to care for these border injury patients and the challenges that exist in their post-discharge care.

Nutritional quality of food purchases during the COVID-19 public health crisis: An analysis of geographic disparities in North Carolina.

Objective: To examine geographic disparities in the nutritional quality of food purchases during the COVID-19 public health crisis in North Carolina (NC). Methods: Using shopper-level longitudinal transaction records between October 2019- and December 2020 from NC's largest grocery retailer, we fit mixed-effect models to examine disparities in the nutritional quality of food purchases among shoppers in counties with different levels of socioeconomic development and how such disparities changed after March 2020, accounting for other observed and contextual factors. Results: Shoppers in counties with lower development levels purchased a larger share of calories from least healthy foods and a smaller share from healthier foods compared to shoppers in counties with higher development levels. These disparities were slightly attenuated for the least healthy foods and did not change for healthier foods after the onset of the COVID crisis. Conclusion: Despite existing nutritional disparities among shoppers in counties with different levels of socioeconomic development, we did not observe a large-scale accentuation of inequities in dietary quality during the COVID-19 crisis. This pattern may have resulted from programmatic responses to mitigate the adverse effects of the COVID crisis on vulnerable populations. Future work should further explore the role of such responses.

Higher ultraviolet light exposure is associated with lower mortality: An analysis of data from the UK biobank cohort study.

We aimed to examine associations between ultraviolet (UV) exposure and mortality among older adults in the United Kingdom (UK). We used data from UK Biobank participants with two UV exposures, validated with measured vitamin D levels: solarium use and annual average residential shortwave radiation. Associations between the UV exposures, all-cause and cause-specific mortality were examined as adjusted hazard ratios. The UV exposures were inversely associated with all-cause, cardiovascular disease (CVD) and cancer mortality. Solarium users were also at a lower risk of non-CVD/non-cancer mortality. The benefits of UV exposure may outweigh the risks in low-sunlight countries.

Rural-urban disparities in cardiovascular disease mortality vary by poverty level and region.

PURPOSE: To examine rural and urban disparities in cardiovascular disease (CVD) death rates by poverty level and region. METHODS: Using 2021 county-level population and mortality data for CVD deaths listed as the underlying cause among adults aged 35-64 years, we calculated age-standardized CVD death rates and rate ratios (RR) for 4 categories of counties: high-poverty rural, high-poverty urban, low-poverty rural, and low-poverty urban (referent). Results are presented nationally and by US Census region. FINDINGS: Rural and urban disparities in CVD mortality varied markedly by poverty and region. Nationally, the CVD death rate was highest among high-poverty rural areas (191 deaths per 100,000, RR: 1.76, CI: 1.73-1.78). By region, Southern high-poverty rural areas had the highest CVD death rate (256 deaths per 100,000) and largest disparity relative to low-poverty urban areas (RR: 2.05; CI: 2.01-2.09). In the Midwest and West, CVD death rates among high-poverty areas were higher than low-poverty areas, regardless of rural or urban classification. CONCLUSIONS: Results reinforce the importance of prioritizing high-poverty rural areas, especially in the South, in efforts to reduce CVD mortality. These efforts may need to consider socioeconomic conditions and region, in addition to rural and urban disparities.

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study.

BACKGROUND: A coordinated care system helps provide timely access to treatment for suspected acute stroke. In Northwestern Ontario (NWO), Canada, communities are widespread with several hospitals offering various diagnostic equipment and services. Thus, resources are limited, and health care providers must often transfer patients with stroke to different hospital locations to ensure the most appropriate care access within recommended time frames. However, health care providers frequently situated temporarily (locum) in NWO or providing care remotely from other areas of Ontario may lack sufficient information and experience in the region to access care for a patient with a time-sensitive condition. Suboptimal decision-making may lead to multiple transfers before definitive stroke care is obtained, resulting in poor outcomes and additional health care system costs. OBJECTIVE: We aimed to develop a tool to inform and assist NWO health care providers in determining the best transfer options for patients with stroke to provide the most efficient care access. We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities. METHODS: Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. These data contained parameters regarding air (Ornge) and land medical transport (3 services), which were preprocessed and cleaned. For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model. RESULTS: In total, 70,623 records were collected in the data set from Ornge and land medical transport services to develop a prediction model. Various learning models were analyzed; all learning models perform better than the simple average of all points in predicting output variables. The decision tree model provided more accurate results than the other models. The decision tree model performed remarkably well, with the values from testing, validation, and the model within a close range. This model was used to develop the "NWO Navigate Stroke" system. The system provides accurate results and demonstrates that a mobile app can be a significant tool for health care providers navigating stroke care in NWO, potentially impacting patient care and outcomes. CONCLUSIONS: The NWO Navigate Stroke system uses a data-driven, reliable, accurate prediction model while considering all variations and is simultaneously linked to all required acute stroke management pathways and tools. It was tested using historical data, and the next step will to involve usability testing with end users.

Comparison of Asthma Phenotypes in Severe Asthma Cohorts (SARP, U-BIOPRED, ProAR and COREA) From 4 Continents.

PURPOSE: Asthma is a clinical syndrome with various underlying pathomechanisms and clinical phenotypes. Genetic, ethnic, and geographic factors may influence the differences in clinical presentation, severity, and prognosis. We compared the characteristics of asthma based on the geographical background by analyzing representative cohorts from the United States, Europe, South America, and Asia using the Severe Asthma Research Program (SARP), Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED), Program for Control of Asthma in Bahia (ProAR), and Cohort for Reality and Evolution of Adult Asthma in Korea (COREA), respectively. METHODS: The clinical characteristics and medications for the SARP (n = 669), U-BIOPRED (n = 509), ProAR (n = 996), and COREA (n = 3,748) were analyzed. Subgroup analysis was performed for severe asthma. RESULTS: The mean age was highest and lowest in the COREA and SARP, respectively. The asthma onset age was lowest in the ProAR. The mean body mass index was highest and lowest in the SARP and COREA, respectively. Baseline pulmonary function was lowest and highest in the U-BIOPRED and COREA, respectively. The number of patients with acute exacerbation in the previous year was highest in U-BIOPRED. The mean blood eosinophil count was highest in COREA. The total immunoglobulin E was highest in the ProAR. The frequency of atopy was highest in the SARP. The principal component analysis plot revealed differences among all cohorts. CONCLUSIONS: The cohorts from 4 different continents exhibited different clinical and physiological characteristics, probably resulting from the interplay between genetic susceptibility and geographical factors.

Evaluation of weather and environmental factors and their association with cutaneous melanoma incidence: A national ecological study.

Background: Cutaneous melanoma (CM) is a significant contributor to skin cancer-related mortality globally and in Canada. Despite the well-established link between ultraviolet (UV) radiation exposure and skin cancer risk, there remains a gap in population-level interventions and persistent misconceptions about sun exposure and impact of environment on individual behavior. Objective: The current study provides an ecological analysis using latest available data (2011-2017) to define geographic/environmental contributors to the CM landscape in Canada. Methods: Utilizing Canadian Cancer Registry and Canadian Urban Environmental Health Research Consortium data, we analyzed 39,605 CM cases occurring in Canada from 2011 to 2017. Environmental data, including UV radiation, greenspace (normalized difference vegetation index), temperature, heat events, and precipitation was used to evaluate the effect of environment on CM incidence rates across Forward Sortation Area postal codes. Results: Forward Sortation Areas with increased CM incidence were associated with higher annual average temperature, snowfall, heat events, normalized difference vegetation index, and vitamin D-weighted UV exposure. Conversely, factors associated with decreased incidence included an increased annual highest temperature, rain precipitation, and a longer duration of heat events. Limitations: This study is subject to ecological bias and findings should be interpreted with caution. Conclusion: This study further substantiates associations between specific environmental factors and CM incidence.

Portraying the developing PCK of Dutch pre-service geography teachers.

Pedagogical Content Knowledge (PCK) is used to describe the knowledge teachers use to teach a specific subject to a specific audience. Although PCK is linked to student success and motivation, relatively little is known about the PCK of geography teachers. Through a mixed methods approach, we surveyed a group of 73 Dutch pre-service teachers in their final year of geography teacher education. We used the PCK-consensus model to address both PCK-on action (teacher knowledge) and PCK-in action (teacher practice). We investigated the former through a CoRe-assignment and the latter through a quantitative survey. Teacher's PCK-in action focussed on teacher-centred lessons with ample attention for visualisations, current events, and efforts to engage students. The results for PCK-on action confirmed the content dependency of PCK. Pre-service teachers chose different geographical topics and used different goals and strategies when teaching these topics. In this context, we also found that they experienced difficulties when teaching controversial issues. In a final step, we combined the results of both methods for 9 teachers in individual PCK portraits. These portraits show that coherence between PCK-elements and, therefore, PCK-quality is still weak for most pre-service teachers. Consequently, their fragile subject matter knowledge seems to influence their developing PCK.

Impact of Location of Residence and Distance to Cancer Centre on Medical Oncology Consultation and Neoadjuvant Chemotherapy for Triple-Negative and HER2-Positive Breast Cancer.

Despite consensus guidelines, most patients with early-stage triple-negative (TN) and HER2-positive (HER2+) breast cancer do not see a medical oncologist prior to surgery and do not receive neoadjuvant chemotherapy (NAC). To understand barriers to care, we aimed to characterize the relationship between geography (region of residence and cancer centre proximity) and receipt of a pre-treatment medical oncology consultation and NAC for patients with TN and HER2+ breast cancer. Using linked administrative datasets in Ontario, Canada, we performed a retrospective population-based analysis of women diagnosed with stage I-III TN or HER2+ breast cancer from 2012 to 2020. The outcomes were a pre-treatment medical oncology consultation and the initiation of NAC. We created choropleth maps to assess the distribution of the outcomes and cancer centres across census divisions. To assess the relationship between distance to the nearest cancer centre and outcomes, we performed multivariable regression analyses adjusted for relevant factors, including tumour extent and nodal status. Of 14,647 patients, 29.9% received a pre-treatment medical oncology consultation and 77.7% received NAC. Mapping demonstrated high interregional variability, ranging across census divisions from 12.5% to 64.3% for medical oncology consultation and from 8.8% to 64.3% for NAC. In the full cohort, compared to a distance of ≤5 km from the nearest cancer centre, only 10-25 km was significantly associated with lower odds of NAC (OR 0.83, 95% CI 0.70-0.99). Greater distances were not associated with pre-treatment medical oncology consultation. The interregional variability in medical oncology consultation and NAC for patients with TN and HER2+ breast cancer suggests that regional and/or provider practice patterns underlie discrepancies in the referral for and receipt of NAC. These findings can inform interventions to improve equitable access to NAC for eligible patients.

Exploring the relationship of rurality and region: An analysis of adolescent marijuana use in the United States.

Marijuana use among adolescents and young adults has increased, however, there is a paucity of research concerning marijuana use among adolescents in rural areas. Current literature holds the assumption that adolescents in rural areas tend to use less marijuana and marijuana associated products compared with youth from urban and suburban areas. However, geographical features may contribute to unique stressors experienced by rural youth, resulting in distinct differences in usage that have been previously unexplored. The purpose of the current study was to explore the relationship between rurality and geographic region by examining patterns of lifetime marijuana use in 12th graders across various geographical backgrounds. Using data from the Monitoring the Future Study database, participants were classified based on rurality (rural, medium suburban/urban, large suburban/urban) and geographic region (Northeast, Midwest, South, West) and data was analyzed to investigate the differences in lifetime marijuana and hash usage. Results demonstrated that rural adolescents in the Northeast and West reported lifetime marijuana and hash product use at the same level as their urban/suburban counterparts; however, there were differences across rurality among Midwest and Southern regions. These results suggest that lifetime marijuana use among rural adolescents is not uniform across geographic regions, indicating that geography should be heavily considered when formulating preventative and educational marijuana programs.

What is a migrant death? An operational definition for a more accurate enumeration of migrant mortality along the US-Mexico border.

Over the last forty years an indeterminate number of persons, ranging from thousands to tens of thousands, have died along the US-Mexico border during migration, fleeing poverty, armed conflict, situations of violence, and disasters. An accurate accounting of migrant deaths along the southern US border is the first step toward an understanding of the extent and the contributing factors of these deaths. In this article, we describe a key aspect of our collaborative work aimed at developing a more representative account of migrant mortality along the southwestern US border: the determination of criteria for inclusion of specific forensic cases as "migrant." Our intention is not to propose a definition of "what is a migrant death" applicable to all contexts and situations but rather one specific to the US-Mexico border region. Our main impetus is to build and launch a web portal to track and map migrant deaths at the US-Mexico border. The criteria we have identified are based on an examination of death data collected by various agencies in the four border states (California, Arizona, New Mexico, and Texas) and at the federal level by the National Missing and Unidentified Persons System (NamUs). They include a) context of human remains discovery; b) identification media/documentation; c) geographic setting; and d) personal effects. Taken together, these criteria will facilitate our determination, case by case, of the probability that human remains found along the United States side of the border may be from a person in the context of migration.

Individual socioeconomic status, neighborhood disadvantage, and cognitive aging: A longitudinal analysis of the CLSA.

BACKGROUND: There are likely many contributors to variation in the rate of cognitive decline in middle and late adulthood, including individual and neighborhood socio-economic factors. This study examines whether individual socio-economic factors, namely income and wealth, correlate with cognitive decline, in part, through neighborhood-level social and material disadvantage. METHODS: Using the three waves of data collection from the Canadian Longitudinal Study on Aging (CLSA), this study included 51,338 participants between the age of 45 and 85 years at baseline (51% female). Individual socio-economic status (SES) was assessed by annual household income and by the current value of savings and investments. Neighborhood disadvantage was measured by area-based material and social deprivation indices. Cognition was measured at each wave using verbal fluency, mental alternations, and delayed word recall. Latent change score models, incorporating direct and indirect pathways, were constructed to estimate the indirect effect of individual SES on cognitive change through area-level disadvantage. Multi-group models were constructed on the basis of age-group (45-64 years; 65-74 years; or 75+ years) to allow for varying estimates across age. RESULTS: Among 45-64-year-olds, income and wealth had indirect effects on initial cognitive level and on rate of cognitive decline through material disadvantage (standardized indirect effects = 0.01, p < 0.001), but only wealth had an indirect effect through social disadvantage (p = 0.019). Among 65-74-year-olds, income and wealth had indirect effects on initial cognitive level (p < 0.01) but not on rate of cognitive decline (p > 0.05), and among 75+ year-olds, no indirect effects were observed (p > 0.05). Wealth and income had direct effects, independent of neighborhood disadvantage, on cognition in all age groups (p < 0.05). CONCLUSIONS: Among middle-aged adults, greater individual SES may mitigate cognitive decline, in part, by allowing individuals to live in more materially and socially advantaged neighborhoods.

Evaluating the Connection Between Rural Travel Time and Health: A Cross-Sectional Analysis of Older Adults Living in the Northeast United States.

INTRODUCTION: To characterize the impact of rural patients' travel time to obtain healthcare on their reported utilization of preventive healthcare services and personal health outcomes. METHODS: Online survey data from rural adults ages 50+ years living in the Northeastern United States were collected from February to August 2021. Study measures included self-reported travel time to obtain healthcare, use of preventive healthcare, and health outcomes. The associations between travel time with use of preventive care and health outcomes were assessed using linear, Poisson, and logistic regression analyses controlling for demographic variables. RESULTS: Our study population included 1052 rural adults, with a mean travel time of 18.5 min (range: 0-60). Travel time was greater for racial/ethnic minority participants and for higher-income participants (both P < .05), but it was not associated with use of preventive healthcare. Greater travel time was associated with poorer mental health and more comorbidities, including cancer and diabetes (all P < .05). CONCLUSIONS: Travel time varied by patient demographic factors, and it was associated with mental health and comorbidities. There was no association between travel time and preventive care use, suggesting that other barriers likely contribute to suboptimal use of these services within rural communities. Further research is needed to elucidate the causal pathways linking travel time to mental health and comorbidities within rural communities, as increased travel may exacerbate intrarural health disparities.

Geotemporal Analysis of Melanoma Incidence and Mortality Identifies Distinct Clusters of Trends within the United States Between 2001 and 2019.

The extent to which the geographic diversity of the US plays a significant role in melanoma incidence and mortality over time has not been precisely characterized. We obtained age-adjusted melanoma data for the 50 states between 2001 and 2019 from the Surveillance, Epidemiology, and End Results registry and performed hierarchical clustering (complete linkage, Euclidean space) to uncover geo-temporal trend groups over 2 decades. While there was a global increase in incidence during this time (b1 = +0.41, P < .0001), there were 6 distinct clusters (by absolute and Z-score) with significantly different temporal trends (analysis of covariance P < .0001). Cluster 2 states had the sharpest increase in incidence with b1 = +0.66, P < .0001. For mortality, the global rate decreased (b1 = -0.03, P = .0003) with 3 and 6 clusters by absolute and Z-scores, respectively (analysis of covariance P < .05). Cluster 1 states exhibited the smallest decline in mortality (b1 = -0.017, P = .008). Mortality to incidence ratios declined (b1 = -0.0037, P < .0001) and harbored 4 and 6 clusters by absolute and Z-score analysis, respectively (analysis of covariance P < .0001). Cluster 4 states had the lowest rate of mortality to incidence ratios decline (b1 = -0.003, P < .0001). These results provide an unprecedented higher dimensional view of melanoma behavior over space and time. With more refined analyses, geospatial studies can uncover local trends which can inform public health agencies to more properly allocate resources.

Putting the exposome into practice: An analysis of the promises, methods and outcomes of the European human exposome network.

OBJECTIVES: Contemporary research on the exposome, i.e. the sum of all the exposures an individual encounters throughout life and that may influence human health, bears the promise of an integrative and policy-relevant research on the effect of environment on health. Critical analyses of the first generation of exposome projects have voiced concerns over their actual breadth of inclusion of environmental factors and a related risk of molecularization of public health issues. The emergence of the European Human Exposome Network (EHEN) provides an opportunity to better situate the ambitions and priorities of the exposome approach on the basis of new and ongoing research. METHODS: We assess the promises, methods, and limitations of the EHEN, as a case study of the second generation of exposome research. A critical textual analysis of profile articles from each of the projects involved in EHEN, published in Environmental Epidemiology, was carried out to derive common priorities, innovations, methodological and conceptual choices across EHEN and to discuss it. RESULTS: EHEN consolidates its integrative outlook by reinforcing the volume and variety of data, its data analysis infrastructure and by diversifying its strategies to deliver actionable knowledge. Yet data-driven limitations severely restrict the geographical and political scope of this knowledge to health issues primarily related to urban setups, which may aggravate some socio-spatial inequalities in health in Europe. CONCLUSIONS: The second generation of exposome research doubles down on the initial ambition of an integrative study of the environmental effects of health to fuel better public health interventions. This intensification is, however, accompanied by significant epistemological challenges and doesn't help to overcome severe restrictions in the geographical and political scope of this knowledge. We thus advocate for increased reflexivity over the limitations of this conceptually and methodologically integrative approach to public and environmental health.