1
|
Cadman T, Strandberg-Larsen K, Calas L, Christiansen M, Culpin I, Dadvand P, de Castro M, Foraster M, Fossati S, Guxens M, Harris JR, Hillegers M, Jaddoe V, Lee Y, Lepeule J, El Marroun H, Maule M, McEachen R, Moccia C, Nader J, Nieuwenhuijsen M, Nybo Andersen AM, Pearson R, Swertz M, Vafeiadi M, Vrijheid M, Wright J, Lawlor DA, Pedersen M. Urban environment in pregnancy and postpartum depression: An individual participant data meta-analysis of 12 European birth cohorts. Environment International 2024; 185:108453. [PMID: 38368715 DOI: 10.1016/j.envint.2024.108453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/17/2024] [Accepted: 01/18/2024] [Indexed: 02/20/2024]
Abstract
BACKGROUND Urban environmental exposures associate with adult depression, but it is unclear whether they are associated to postpartum depression (PPD). OBJECTIVES We investigated associations between urban environment exposures during pregnancy and PPD. METHODS We included women with singleton deliveries to liveborn children from 12 European birth cohorts (N with minimum one exposure = 30,772, analysis N range 17,686-30,716 depending on exposure; representing 26-46 % of the 66,825 eligible women). We estimated maternal exposure during pregnancy to ambient air pollution with nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10), road traffic noise (Lden), natural spaces (Normalised Difference Vegetation Index; NDVI, proximity to major green or blue spaces) and built environment (population density, facility richness and walkability). Maternal PPD was assessed 3-18 months after birth using self-completed questionnaires. We used adjusted logistic regression models to estimate cohort-specific associations between each exposure and PPD and combined results via meta-analysis using DataSHIELD. RESULTS Of the 30,772 women included, 3,078 (10 %) reported having PPD. Exposure to PM10 was associated with slightly increased odds of PPD (adjusted odd ratios (OR) of 1.08 [95 % Confidence Intervals (CI): 0.99, 1.17] per inter quartile range increment of PM10) whilst associations for exposure to NO2 and PM2.5 were close to null. Exposure to high levels of road traffic noise (≥65 dB vs. < 65 dB) was associated with an OR of 1.12 [CI: 0.95, 1.32]. Associations between green spaces and PPD were close to null; whilst proximity to major blue spaces was associated with increased risk of PPD (OR 1.12, 95 %CI: 1.00, 1.26). All associations between built environment and PPD were close to null. Multiple exposure models showed similar results. DISCUSSION The study findings suggest that exposure to PM10, road traffic noise and blue spaces in pregnancy may increase PPD risk, however future studies should explore this causally.
Collapse
Affiliation(s)
- Tim Cadman
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark; Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, the Netherlands; Department of Social Medicine, School of Medicine, University of Crete, Greece.
| | - Katrine Strandberg-Larsen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Lucinda Calas
- Inserm, UMR1153 Center for Research in Epidemiology and Statistics (CRESS), Early Life Research on Later Health Team (EARoH), Paris, France
| | - Malina Christiansen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Iryna Culpin
- MRC Integrative Epidemiology Unit at the University of Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, United Kingdom
| | - Payam Dadvand
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5. Pabellón 11, 28029 Madrid, Spain
| | - Montserrat de Castro
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5. Pabellón 11, 28029 Madrid, Spain
| | - Maria Foraster
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5. Pabellón 11, 28029 Madrid, Spain
| | - Serena Fossati
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5. Pabellón 11, 28029 Madrid, Spain
| | - Mònica Guxens
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5. Pabellón 11, 28029 Madrid, Spain; Department of Child and Adolescent Psychiatry, University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Jennifer R Harris
- Center for Fertility and Health, Norwegian Institute of Public Health, Olso, Norway
| | - Manon Hillegers
- Department of Child and Adolescent Psychiatry, University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Vincent Jaddoe
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - Yunsung Lee
- Center for Fertility and Health, Norwegian Institute of Public Health, Olso, Norway
| | - Johanna Lepeule
- Université Grenoble Alpes INSERM CNRS Institute for Advanced Biosciences Team of Environmental Epidemiology Applied to Development and Respiratory Health, F-38700 La Tronche, France
| | - Hanan El Marroun
- Department of Child and Adolescent Psychiatry, University Medical Center, Erasmus MC, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, the Netherlands
| | - Milena Maule
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy
| | - Rosie McEachen
- Bradford Institute for Health Research, Bradford BD9 6RJ, United Kingdom
| | - Chiara Moccia
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy
| | - Johanna Nader
- Department of Genetics and Bioinformatics, Division of Health Data and Digitalisation, Norwegian Institute of Public Health, Oslo, Norway
| | - Mark Nieuwenhuijsen
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5. Pabellón 11, 28029 Madrid, Spain
| | - Anne-Marie Nybo Andersen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Rebecca Pearson
- MRC Integrative Epidemiology Unit at the University of Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, United Kingdom; Manchester Metropolitan University, All Saints Building, All Saints, Manchester, United Kingdom
| | - Morris Swertz
- Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Marina Vafeiadi
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Martine Vrijheid
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5. Pabellón 11, 28029 Madrid, Spain
| | - John Wright
- Bradford Institute for Health Research, Bradford BD9 6RJ, United Kingdom
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, United Kingdom
| | - Marie Pedersen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
2
|
Cadman T, Elhakeem A, Vinther JL, Avraam D, Carrasco P, Calas L, Cardo M, Charles MA, Corpeleijn E, Crozier S, de Castro M, Estarlich M, Fernandes A, Fossatti S, Gruszfeld D, Gurlich K, Grote V, Haakma S, Harris JR, Heude B, Huang RC, Ibarluzea J, Inskip H, Jaddoe V, Koletzko B, Luque V, Manios Y, Moirano G, Moschonis G, Nader J, Nieuwenhuijsen M, Andersen AMN, McEachen R, de Moira AP, Popovic M, Roumeliotaki T, Salika T, Marina LS, Santos S, Serbert S, Tzorovili E, Vafeiadi M, Verduci E, Vrijheid M, Vrijkotte TGM, Welten M, Wright J, Yang TC, Zugna D, Lawlor D. Associations of Maternal Educational Level, Proximity to Greenspace During Pregnancy, and Gestational Diabetes With Body Mass Index From Infancy to Early Adulthood: A Proof-of-Concept Federated Analysis in 18 Birth Cohorts. Am J Epidemiol 2023:kwad206. [PMID: 37856700 DOI: 10.1093/aje/kwad206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 04/06/2023] [Indexed: 10/21/2023] Open
Abstract
International sharing of cohort data for research is important and challenging. We explored the feasibility of multi-cohort federated analyses by examining associations between three pregnancy exposures (maternal education, exposure to green vegetation and gestational diabetes) with offspring BMI from infancy to 17 years. We used data from 18 cohorts (n=206,180 mother-child pairs) from the EU Child Cohort Network and derived BMI at ages 0-1, 2-3, 4-7, 8-13 and 14-17 years. Associations were estimated using linear regression via one-stage IPD meta-analysis using DataSHIELD. Associations between lower maternal education and higher child BMI emerged from age 4 and increased with age (difference in BMI z-score comparing low with high education age 2-3 years = 0.03 [95% CI 0.00, 0.05], 4-7 years = 0.16 [95% CI 0.14, 0.17], 8-13 years = 0.24 [95% CI 0.22, 0.26]). Gestational diabetes was positively associated with BMI from 8 years (BMI z-score difference = 0.18 [CI 0.12, 0.25]) but not at younger ages; however associations attenuated towards the null when restricted to cohorts which measured GDM via universal screening. Exposure to green vegetation was weakly associated with higher BMI up to age one but not at older ages. Opportunities of cross-cohort federated analyses are discussed.
Collapse
|