Objectives, design and main findings until 2020 from the Rotterdam Study

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Abstract

The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.

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Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project.

Marloes Eeftens, Rob Beelen, Kees de Hoogh … (2012)

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

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Contributors

M. Arfan Ikram: m.a.ikram@erasmusmc.nl

Journal

Journal ID (nlm-ta): Eur J Epidemiol

Journal ID (iso-abbrev): Eur. J. Epidemiol

Title: European Journal of Epidemiology

Publisher: Springer Netherlands (Dordrecht )

ISSN (Print): 0393-2990

ISSN (Electronic): 1573-7284

Publication date (Electronic): 4 May 2020

Publication date PMC-release: 4 May 2020

Publication date (Print): 2020

Volume: 35

Issue: 5

Pages: 483-517

Affiliations

[1 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Epidemiology, , Erasmus University Medical Center, ; PO Box 2040, 3000 CA Rotterdam, The Netherlands

[2 ]GRID grid.410566.0, ISNI 0000 0004 0626 3303, Department of Respiratory Medicine, , Ghent University Hospital, ; Ghent, Belgium

[3 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Otorhinolaryngology, , Erasmus University Medical Center, ; Rotterdam, The Netherlands

[4 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Neurology, , Erasmus University Medical Center, ; Rotterdam, The Netherlands

[5 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Ophthalmology, , Erasmus University Medical Center, ; Rotterdam, The Netherlands

[6 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Gastroenterology, , Erasmus University Medical Center, ; Rotterdam, The Netherlands

[7 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Internal Medicine, , Erasmus University Medical Center, ; Rotterdam, The Netherlands

[8 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Dermatology, , Erasmus University Medical Center, ; Rotterdam, The Netherlands

[9 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Radiology and Nuclear Medicine, , Erasmus University Medical Center, ; Rotterdam, The Netherlands

Article

Publisher ID: 640

DOI: 10.1007/s10654-020-00640-5

PMC ID: 7250962

PubMed ID: 32367290

SO-VID: 80e91d38-3282-4a84-b6e6-872866b0a606

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 23 January 2020

Date accepted : 23 April 2020

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ScienceOpen disciplines: Public health

Keywords: biomarkers,cancer and related diseases,cardiovascular diseases,cohort study,dermatological diseases,endocrine diseases,epidemiologic methods,genetic and molecular epidemiology,nutrition and lifestyle epidemiology,liver diseases,neurological diseases,oncology,ophthalmic diseases,otolaryngological diseases,pharmacoepidemiology,population imaging,renal diseases,psychiatric diseases,respiratory diseases

Objectives, design and main findings until 2020 from the Rotterdam Study

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Most cited references 409

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Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project.

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