Abstract
We examined the long-term association between objective neighbourhood sociodemographic characteristics (index of socioeconomic position (SEP), average income, percent low-income earners, average house price, percent immigrants and urban density) with depressive and anxiety symptoms, covering five 3-year waves of the Longitudinal Aging Study Amsterdam (n = 3,772). Multi-level regression models assessed each neighbourhood-level characteristic separately, adjusting for individual-level covariates. A higher percentage of immigrants and higher urban density, but not other neighbourhood characteristics, were significantly associated with depressive and anxiety symptoms over time in models adjusted for individual SEP. Results of time interaction models indicated that the associations were stable over the 15-year period.
| Original language | English |
|---|---|
| Article number | 102172 |
| Pages (from-to) | 102172 |
| Journal | Health and Place |
| Volume | 59 |
| DOIs | |
| Publication status | Published - Sept 2019 |
Bibliographical note
Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.Funding
The Longitudinal Aging Study Amsterdam (LASA) is financially supported by the Netherlands Ministry of Health, Welfare and Sports, Directorate of Long-Term Care. The data collection in 2012/2013 was financially supported by the Netherlands Organization for Scientific Research (NWO) in the framework of the project “New cohorts of young-old in the 21st century” (file number 480-10-014). The funder had no role in the design, execution, analysis or interpretation of the data, or writing of the manuscript. I. Motoc is employed through the MINDMAP project. MINDMAP is funded by the European Commission HORIZON 2020 research and innovation action 667661. The area-level data was obtained from the Geoscience and Health Cohort Consortium (GECCO) project which is financially supported by the EMGO Institute for Health and Care Research of Vrije Universiteit Amsterdam and VU University Medical Center in Amsterdam, the Netherlands. We would like to acknowledge the support of Jos Twisk who provided statistical advice. We also would like to thank the Institute for Risk Assessment Sciences of the Utrecht University and the coordinating center of the European Study of Cohorts for Air Pollution Effects (ESCAPE), for providing data on air pollution. Furthermore, we would like to thank the Netherlands Environmental Assessment Agency for providing data on road-traffic, rail-traffic and air-traffic noise. The Longitudinal Aging Study Amsterdam (LASA) is financially supported by the Netherlands Ministry of Health, Welfare and Sports , Directorate of Long-Term Care. The data collection in 2012/2013 was financially supported by the Netherlands Organization for Scientific Research (NWO) in the framework of the project “New cohorts of young-old in the 21st century” (file number 480-10-014 ). The funder had no role in the design, execution, analysis or interpretation of the data, or writing of the manuscript. I. Motoc is employed through the MINDMAP project. MINDMAP is funded by the European Commission HORIZON 2020 research and innovation action 667661 . The area-level data was obtained from the Geoscience and Health Cohort Consortium (GECCO) project which is financially supported by the EMGO Institute for Health and Care Research of Vrije Universiteit Amsterdam and VU University Medical Center in Amsterdam, the Netherlands.
| Funders | Funder number |
|---|---|
| Geoscience and Health Cohort Consortium | |
| Institute for Risk Assessment Sciences of the Utrecht University | |
| Netherlands Ministry of Health, Welfare and Sports , Directorate of Long-Term Care | |
| Netherlands Ministry of Health, Welfare and Sports, Directorate of Long-Term Care | |
| Horizon 2020 Framework Programme | |
| European Commission | 667661 |
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek | 480-10-014 |
| Planbureau voor de Leefomgeving |
