Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project

Evangelia Samoli; Sophia Rodopoulou; Ulla A Hvidtfeldt; Kathrin Wolf; Massimo Stafoggia; Bert Brunekreef; Maciej Strak; Jie Chen; Zorana J Andersen; Richard Atkinson; Mariska Bauwelinck; Tom Bellander; Jørgen Brandt; Giulia Cesaroni; Francesco Forastiere; Daniela Fecht; John Gulliver; Ole Hertel; Barbara Hoffmann; Kees de Hoogh; Nicole A.H Janssen; Matthias Ketzel; Jochem O Klompmaker; Shuo Liu; Petter Ljungman; Gabriele Nagel; Bente Oftedal; Göran Pershagen; Annette Peters; Ole Raaschou-Nielsen; Matteo Renzi; Doris T Kristoffersen; Gianluca Severi; Torben Sigsgaard; Danielle Vienneau; Gudrun Weinmayr; Gerard Hoek; Klea Katsouyanni

doi:10.1016/j.envint.2020.106371

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Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project

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Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project

Evangelia Samoli, Sophia Rodopoulou, Ulla A Hvidtfeldt, Kathrin Wolf, Massimo Stafoggia, Bert Brunekreef, Maciej Strak, Jie Chen, Zorana J Andersen, Richard Atkinson, …

Environment international, Vol.147, 106371

02/2021

DOI: https://doi.org/10.1016/j.envint.2020.106371

PMID: 33422970

Abstract

Health effects

Multi-level analysis

Cox model

Mixed models

Frailty models

Air Pollution

We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM2.5 and NO2) and health (natural-cause mortality and cerebrovascular, coronary and lung cancer incidence). We applied five approaches in a multivariable Cox model to account for the first level of clustering corresponding to cohort specification: (1) not accounting for the cohort or using (2) indicator variables, (3) strata, (4) a frailty term in frailty Cox models, (5) a random intercept under a mixed Cox, for cohort identification. We accounted for the second level of clustering due to common characteristics in the residential area by (1) a random intercept per small area or (2) applying variance correction. We assessed the stratified, frailty and mixed Cox approach through simulations under different scenarios for heterogeneity in the underlying hazards and the air pollution effects. Effect estimates were stable under approaches used to adjust for cohort but substantially differed when no adjustment was applied. Further adjustment for the small area grouping increased the effect estimates’ standard errors. Simulations confirmed identical results between the stratified and frailty models. In ELAPSE we selected a stratified multivariable Cox model to account for between-cohort heterogeneity without adjustment for small area level, due to the small number of subjects and events in the latter. Our study supports the need to account for between-cohort heterogeneity in multi-center collaborations using pooled individual level data.

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Title: Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project
Creators: Evangelia Samoli - Dept. of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 75 Mikras Asias Str, 115 27 Athens, Greece
Sophia Rodopoulou - Dept. of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 75 Mikras Asias Str, 115 27 Athens, Greece
Ulla A Hvidtfeldt - Danish Cancer Society Research Centre, Copenhagen, Denmark
Kathrin Wolf - Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
Massimo Stafoggia - Department of Epidemiology, Lazio Region Health Service ASL Roma 1, Rome, Italy
Bert Brunekreef - Institute for Risk Assessment Sciences (IRAS), Utrecht University, Postbus 80125, 3508 TC Utrecht, the Netherlands
Maciej Strak - Institute for Risk Assessment Sciences (IRAS), Utrecht University, Postbus 80125, 3508 TC Utrecht, the Netherlands
Jie Chen - Institute for Risk Assessment Sciences (IRAS), Utrecht University, Postbus 80125, 3508 TC Utrecht, the Netherlands
Zorana J Andersen - University of Copenhagen, Department of Public Health, Section of Environmental Health, Øster Farimagsgade 5, 1014, Copenhagen, Denmark
Richard Atkinson - Population Health Research Institute, St George’s, University of London, Cranmer Terrace, London SW17 0RE, UK
Mariska Bauwelinck - Interface Demography, Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium
Tom Bellander - Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
Jørgen Brandt - Department of Environmental Science, Aarhus University, Frederiksborgvej 399, Roskilde, Denmark
Giulia Cesaroni - Department of Epidemiology, Lazio Region Health Service ASL Roma 1, Rome, Italy
Francesco Forastiere - NIHR HPRU Health Impact of Environmental Hazards, Environmental Research Group, Analytical, Environmental & Forensic Sciences, King's College London, UK
Daniela Fecht - Small Area Health Statistics Unit, MRC Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London W2 1PG, UK
John Gulliver - Centre for Environmental Health and Sustainability & School of Geography, Geology and the Environment, University of Leicester, Leicester, UK
Ole Hertel - Department of Environmental Science, Aarhus University, Frederiksborgvej 399, Roskilde, Denmark
Barbara Hoffmann - Institute for Occupational, Social and Environmental Medicine, Medical Faculty, Heinrich-Heine-University of Düsseldorf, Germany
Kees de Hoogh - Swiss Tropical and Public Health Institute, Basel, Switzerland
Nicole A.H Janssen - Institute for Risk Assessment Sciences (IRAS), Utrecht University, Postbus 80125, 3508 TC Utrecht, the Netherlands
Matthias Ketzel - Department of Environmental Science, Aarhus University, Frederiksborgvej 399, Roskilde, Denmark
Jochem O Klompmaker - Institute for Risk Assessment Sciences (IRAS), Utrecht University, Postbus 80125, 3508 TC Utrecht, the Netherlands
Shuo Liu - University of Copenhagen, Department of Public Health, Section of Environmental Health, Øster Farimagsgade 5, 1014, Copenhagen, Denmark
Petter Ljungman - Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
Gabriele Nagel - Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
Bente Oftedal - Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
Göran Pershagen - Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
Annette Peters - Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
Ole Raaschou-Nielsen - Danish Cancer Society Research Centre, Copenhagen, Denmark
Matteo Renzi - Department of Epidemiology, Lazio Region Health Service ASL Roma 1, Rome, Italy
Doris T Kristoffersen - Cluster for Health Services Research, Norwegian Institute of Public Health, Oslo, Norway
Gianluca Severi - Department of Epidemiology, Lazio Region Health Service ASL Roma 1, Rome, Italy
Torben Sigsgaard - Department of Public Health, Environment Occupation and Health, Danish Ramazzini Centre, Aarhus University, Aarhus, Denmark
Danielle Vienneau - Swiss Tropical and Public Health Institute, Basel, Switzerland
Gudrun Weinmayr - Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
Gerard Hoek - Institute for Risk Assessment Sciences (IRAS), Utrecht University, Postbus 80125, 3508 TC Utrecht, the Netherlands
Klea Katsouyanni - Dept. of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 75 Mikras Asias Str, 115 27 Athens, Greece
Publication Details: Environment international, Vol.147, 106371
Publisher: Elsevier Ltd
Date published: 02/2021
Date accepted: 25/12/2020
Grant note: This work was supported by Health Effects Institute (HEI) Research Agreement [grant number #4954-RFA14-3/16-5-3].
Identifiers: 99542121902346
Academic Unit: School of Sustainability, Civil and Environmental Engineering
Language: English
Resource Type: Journal article
SDG (Scopus 2023): SDG 3

Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project

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