Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Mais filtros

Base de dados
Intervalo de ano de publicação
BMJ Open ; 8(6): e021597, 2018 Jun 09.
Artigo em Inglês | MEDLINE | ID: mdl-29886447


PURPOSE: In the Netherlands, a great variety of objectively measured geo-data is available, but these data are scattered and measured at varying spatial and temporal scales. The centralisation of these geo-data and the linkage of these data to individual-level data from longitudinal cohort studies enable large-scale epidemiological research on the impact of the environment on public health in the Netherlands. In the Geoscience and Health Cohort Consortium (GECCO), six large-scale and ongoing cohort studies have been enriched with a variety of existing geo-data. Here, we introduce GECCO by describing: (1) the phenotypes of the involved cohort studies, (2) the collected geo-data and their sources, (3) the methodology that was used to link the collected geo-data to individual cohort studies, (4) the similarity of commonly used geo-data between our consortium and the nationwide situation in the Netherlands and (5) the distribution of geo-data within our consortium. PARTICIPANTS: GECCO includes participants from six prospective cohort studies (eg, 44 657 respondents (18-100 years) in 2006) and it covers all municipalities in the Netherlands. Using postal code information of the participants, geo-data on the address-level, postal code-level as well as neighbourhood-level could be linked to individual-level cohort data. FINDINGS TO DATE: The geo-data could be successfully linked to almost all respondents of all cohort studies, with successful data-linkage rates ranging from 97.1% to 100.0% between cohort studies. The results show variability in geo-data within and across cohorts. GECCO increases power of analyses, provides opportunities for cross-checking and replication, ensures sufficient geographical variation in environmental determinants and allows for nuanced analyses on specific subgroups. FUTURE PLANS: GECCO offers unique opportunities for (longitudinal) studies on the complex relationships between the environment and health outcomes. For example, GECCO will be used for further research on environmental determinants of physical/psychosocial functioning and lifestyle behaviours.

Psychol Med ; : 1-13, 2018 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-29540253


BACKGROUND: Which neighbourhood factors most consistently impact on depression and anxiety remains unclear. This study examines whether objectively obtained socioeconomic, physical and social aspects of the neighbourhood in which persons live are associated with the presence and severity of depressive and anxiety disorders. METHODS: Cross-sectional data are from the Netherlands Study of Depression and Anxiety including participants (n = 2980) with and without depressive and anxiety disorders in the past year (based on DSM-based psychiatric interviews). We also determined symptom severity of depression (Inventory of Depression Symptomatology), anxiety (Beck Anxiety Inventory) and fear (Fear Questionnaire). Neighbourhood characteristics comprised socioeconomic factors (socioeconomic status, home value, number of social security beneficiaries and percentage of immigrants), physical factors (air pollution, traffic noise and availability of green space and water) and social factors (social cohesion and safety). Multilevel regression analyses were performed with the municipality as the second level while adjusting for individual sociodemographic variables and household income. RESULTS: Not urbanization grade, but rather neighbourhood socioecononomic factors (low socioeconomic status, more social security beneficiaries and more immigrants), physical factors (high levels of traffic noise) and social factors (lower social cohesion and less safety) were associated with the presence of depressive and anxiety disorders. Most of these neighbourhood characteristics were also associated with increased depressive and anxiety symptoms severity. CONCLUSION: These findings suggest that it is not population density in the neighbourhood, but rather the quality of socioeconomic, physical and social neighbourhood characteristics that is associated with the presence and severity of affective disorders.