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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.
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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
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Shen J, Wang Y. Allocating and mapping ecosystem service demands with spatial flow from built-up areas to natural spaces. Sci Total Environ 2021; 798:149330. [PMID: 34340066 DOI: 10.1016/j.scitotenv.2021.149330] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 07/15/2021] [Accepted: 07/24/2021] [Indexed: 06/13/2023]
Abstract
Co-urbanized areas around large cities in developing countries face the problem of spatial disconnection between supply and demand areas of ecosystem services (ES). To explore the reflection of human needs in the nonadjacent surrounding natural spaces and identify the response of the existing natural space system to the ES demand in terms of total amount and spatial distribution, a new method for ES demand mapping in co-urbanized areas was proposed. Based on the theory of the ES delivery chain, urban built-up areas are identified as service benefiting areas (SBAs) and the sources where demands are generated, natural spaces are regarded as service provision areas (SPAs) and the sinks and destinations where demands are satisfied, and ES spatial flow is considered as the delivery mechanism and ecological process that promotes the demand flow from sources to sinks. An indicator cluster composed of four multidimensional indicators, including flow quantity, flow boundary, flow direction and allocation mode along the distance, was used to characterize the spatial flow and represent the four key links in the technical path of allocating ES demand from built-up areas to natural spaces with spatial flow to intuitively reflect the spatial characteristics of human social demands projected in them. We quantified and mapped the distribution of three ES demands in built-up areas and surrounding natural spaces. In the former, the high-demand spaces are concentrated in the areas with high population density or high aging degree; while in the latter, the high-demand spaces are mainly adjacent to the built-up areas or the large-scale natural spaces. By controlling the flow quantity, expanding the flow area, increasing the flow directions and improving the ES supply capacity of SPAs within a given distance, the high ES demands in the above spaces can be effectively regulated.
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Affiliation(s)
- Jiake Shen
- Department of Urban Planning, College of Architecture and Urban Planning, Tongji University, No. 1239 Siping Rd., Shanghai 200092, China
| | - Yuncai Wang
- Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, No. 1239 Siping Rd., Shanghai 200092, China; Joint Laboratory of Ecological Urban Design (Research Centre for Land Ecological Planning, Design and Environmental Effects, International Joint Research Centre of Urban-Rural Ecological Planning and Design), College of Architecture and Urban Planning, Tongji University, No. 1239 Siping Rd., Shanghai 200092, China.
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Rugel EJ, Brauer M. Quiet, clean, green, and active: A Navigation Guide systematic review of the impacts of spatially correlated urban exposures on a range of physical health outcomes. Environ Res 2020; 185:109388. [PMID: 32244108 DOI: 10.1016/j.envres.2020.109388] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 02/23/2020] [Accepted: 03/12/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Recent epidemiologic analyses have considered impacts of multiple spatially correlated urban exposures, but this literature has not been systematically evaluated. OBJECTIVES To characterize the long-term impacts of four distinct spatially correlated urban environmental exposures - traffic-related air pollution (TRAP), noise, natural spaces, and neighborhood walkability - by evaluating studies including measures of at least two such exposures in relationship to mortality, cardiovascular disease, chronic respiratory disease, allergy, type 2 diabetes, or reproductive outcomes. METHODS Following the Navigation Guide framework, the literature was searched for studies published since 2003 and meeting predefined inclusion criteria. Identified studies were scored individually for risk of bias and all studies related to an exposure-group set were appraised for overall quality and strength of evidence. RESULTS A total of 51 individual studies (TRAP and noise: n = 29; TRAP and natural spaces: n = 10; noise and natural spaces: n = 2; TRAP, noise, and natural spaces: n = 7; TRAP, noise, natural spaces, and walkability: n = 3) were included. When TRAP and noise were considered jointly, evidence was sufficient for increased cardiovascular morbidity with higher noise exposures; sufficient for no effect of TRAP on CVD morbidity; sufficient for increased mortality with higher TRAP exposures, but limited for noise; and limited for increased adverse reproductive outcomes with higher TRAP exposures and no effect of noise. Looking at natural spaces and TRAP, there was limited evidence for lower risk of chronic respiratory disease and small increases in birthweight with greater natural space; this relationship with birthweight persisted after adjustment for noise as well. Evidence was inadequate for all other exposure groups and outcomes. DISCUSSION Studies that properly account for the complexity of relationships between urban form and physical health are limited but suggest that even highly correlated exposures may have distinct effects. REVIEW REGISTRATION PROSPERO 2018 CRD42018106050.
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Affiliation(s)
- Emily Jessica Rugel
- School of Population and Public Health, University of British Columbia, 3rd Floor - 2206 East Mall, Vancouver, BC V6T1Z3, Canada
| | - Michael Brauer
- School of Population and Public Health, University of British Columbia, 3rd Floor - 2206 East Mall, Vancouver, BC V6T1Z3, Canada; Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA 98121, USA.
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