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This special issue deals with temporalities in migration law with particular emphasis on the European context. At the crossroads of several legal fields, including public law, human rights law, EU law and public international law, the topic is cutting-edge in migration law. The articles collected were originally presented at a conference organized at Vrije Universiteit in Amsterdam in June 2023 and another organized at Uppsala University in September 2024, both dealing with time and temporalities in migration law from a variety of perspectives. The aim of these conferences was to further develop the study of the roles of time in European migration law by unpacking the diversity of ways in which time works as an instrument of migration control in Europe. While temporal governance is far from limited to the European context – the US ‘remain in Mexico’ policy7 and the Australian temporary protection visa8 being only two examples – Europe is an interesting site of analysis. It is a forerunner in creating ‘innovative’ migration control policies9; it combines opposites, such as unhindered international movement within Europe for some, e.g., European citizens, alongside fierce immobility and stuckedness for others; it is characterized by a multilevel interplay marking the complexities of interaction between a multitude of different legal regimes and jurisdictions – domestic, EU and international (including the ECHR) – with strong human rights institutions and frameworks. This combination makes Europe a privileged site of inquiry. Drawing on this ‘forerunner quality’ and characterizing elements, this Introduction poses the question whether it is possible to distinguish a form of time one could call ‘European time’ to describe a specifically European approach to implementing temporal governance techniques in the field of migration.

Studies on neighbourhood characteristics and depression show equivocal results.AimsThis large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression. Cross-sectional design including data are from eight Dutch cohort studies (n = 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis. The pooled analysis showed that higher urbanisation grade (odds ratio (OR) = 1.05, 95% CI 1.01-1.10), lower socioeconomic status (OR = 0.90, 95% CI 0.87-0.95), higher number of social security beneficiaries (OR = 1.12, 95% CI 1.06-1.19), higher percentage of non-Dutch residents (OR = 1.08, 95% CI 1.02-1.14), higher levels of air pollution (OR = 1.07, 95% CI 1.01-1.12), less green space (OR = 0.94, 95% CI 0.88-0.99) and less social safety (OR = 0.92, 95% CI 0.88-0.97) were associated with higher prevalence of depression. All four socioeconomic neighbourhood characteristics and social safety were also consistently associated with continuous depression severity scores. This large-scale pooled analysis across eight Dutch cohort studies shows that urbanisation and various socioeconomic, physical and social neighbourhood characteristics are associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health.Declaration of interestNone.

Environmental exposures are increasingly investigated as possible drivers of health behaviours and disease outcomes. So-called exposome studies that aim to identify and better understand the effects of exposures on behaviours and disease risk across the life course require high-quality environmental exposure data. The Netherlands has a great variety of environmental data available, including high spatial and often temporal resolution information on urban infrastructure, physico-chemical exposures, presence and availability of community services, and others. Until recently, these environmental data were scattered and measured at varying spatial scales, impeding linkage to individual-level (cohort) data as they were not operationalised as personal exposures, that is, the exposure to a certain environmental characteristic specific for a person. Within the Geoscience and hEalth Cohort COnsortium (GECCO) and with support of the Global Geo Health Data Center (GGHDC), a platform has been set up in The Netherlands where environmental variables are centralised, operationalised as personal exposures, and used to enrich 23 cohort studies and provided to researchers upon request. We here present and detail a series of personal exposure data sets that are available within GECCO to date, covering personal exposures of all residents of The Netherlands (currently about 17 M) over the full land surface of the country, and discuss challenges and opportunities for its use now and in the near future.

Abstract Background Evidence from the United States and United Kingdom suggests that ethnic minority populations are at an increased risk for developing severe coronavirus disease 2019 (COVID-19); however, data from other West-European countries are scarce. Methods We analyzed data from 1439 patients admitted between February 2020 and January 2021 to 4 main hospitals in Amsterdam and Almere, the Netherlands. Differences in the risk for hospitalization were assessed by comparing demographics to the general population. Using a population-based cohort as reference, we determined differences in the association between comorbidities and COVID-19 hospitalization. Outcomes after hospitalization were analyzed using Cox regression. Results The hospitalization risk was higher in all ethnic minority groups than in those of Dutch origin, with age-adjusted odds ratios ranging from 2.2 (95% confidence interval [CI], 1.7–2.6) in Moroccans to 4.5 (95% CI, 3.2–6.0) in Ghanaians. Hypertension and diabetes were similarly associated with COVID-19 hospitalization. For all other comorbidities, we found differential associations. Intensive care unit admission and mortality during 21-day follow-up after hospitalization was comparable between ethnicities. Conclusions The risk of COVID-19 hospitalization was higher in all ethnic minority groups compared to the Dutch, but the risk of adverse outcomes after hospitalization was similar. Our results suggest that these inequalities may in part be attributable to comorbidities that can be prevented by targeted public health prevention measures. More work is needed to gain insight into the role of other potential factors such as social determinants of health, which might have contributed to the ethnic inequalities in COVID-19 hospitalization.