Evidence map›Paper›PMID 34740291›Full record

ArticleEnvironmental pollution (Barking, Essex : 1987)2021

Early life exposure to greenness and executive function and behavior: An application of inverse probability weighting of marginal structural models.

Marcia P Jimenez, Izzuddin M Aris, Sheryl Rifas-Shiman, Jessica Young, Henning Tiemeier, Marie-France Hivert, Emily Oken, Peter James

Abstract read
In one paragraph

Article in Environmental pollution (Barking, Essex : 1987), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Marcia P JimenezDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: mpjimenez@hsph.harvard.edu.
Izzuddin M ArisDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA. Electronic address: Izzuddin_Aris@harvardpilgrim.org.
Sheryl Rifas-ShimanDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA. Electronic address: sheryl_rifas@harvardpilgrim.org.
Jessica YoungDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: jyoung@hsph.harvard.edu.
Henning TiemeierDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: tiemeier@hsph.harvard.edu.
Marie-France HivertDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA. Electronic address: mhivert@partners.org.
Emily OkenDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: emily_oken@harvardpilgrim.org.
Peter JamesDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: pjames@hsph.harvard.edu.

Funding

Prenatal environmental determinants of health in young adulthood: a lifecourse approachR01HD034568 · NICHD · HARVARD PILGRIM HEALTH CARE, INC. · PI Marie-France Hivert, Emily Oken · 1998 to 2026
$20.6M
Common and distinct early environmental influences on cardiometabolic and respiratory health: Mechanisms and methodsUH3OD023286 · OD · HARVARD PILGRIM HEALTH CARE, INC. · PI OKEN, EMILY · 2018 to 2022
$11.7M
Common and distinct early environmental influences on cardiometabolic and respiratory health: Mechanisms and methodsUG3OD023286 · OD · HARVARD PILGRIM HEALTH CARE, INC. · PI KLEINMAN, KENNETH P., OKEN, EMILY · 2016 to 2017
$4.1M
Built Environment Assessment through Computer visiON (BEACON): Applying Deep Learning to Street-Level and Satellite Images to Estimate Built Environment Effects on Cardiovascular HealthR01HL150119 · NHLBI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI JAMES, PETER · 2020 to 2024
$3.9M
High Resolution Measures of Behavioral Cancer Risk Factors From Mobile TechnologyR00CA201542 · NCI · HARVARD PILGRIM HEALTH CARE, INC. · PI JAMES, PETER · 2017 to 2019
$747k
Neurodegenerative diseases and the role of green space: A deep learning assessmentR00AG066949 · NIA · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI PESCADOR JIMENEZ, MARCIA IXCHEL · 2022 to 2024
$738k
Neurodegenerative diseases and the role of green space: A deep learning assessmentK99AG066949 · NIA · HARVARD SCHOOL OF PUBLIC HEALTH · PI PESCADOR JIMENEZ, MARCIA IXCHEL · 2020 to 2021
$248k
NCI NIH HHS R00 CA201542NHLBI NIH HHS R01 HL150119NIA NIH HHS K99 AG066949NIA NIH HHS R00 AG066949NICHD NIH HHS R01 HD034568NIH HHS UG3 OD023286NIH HHS UH3 OD023286
6 · The paper itself

Abstract

Increasingly, studies suggest benefits of natural environments or greenness on children's health. However, little is known about cumulative exposure or windows of susceptibility to greenness exposure. Using inverse probability weighting of marginal structural models (IPW/MSM), we estimated effects of greenness exposure from birth through adolescence on executive function and behavior. We analyzed data of 908 children from Project Viva enrolled at birth in 1999-2002 and followed up until early adolescence. In mid-childhood (median 7.7 years) and early adolescence (13.1 years), executive function and behavior were assessed using the Behavior Rating Inventory of Executive Function and the Strengths and Difficulties Questionnaire (SDQ). Greenness was measured at birth, early childhood, mid-childhood, and early adolescence, using the Normalized Difference Vegetation Index. We used inverse probability weighting of marginal structural models to estimate effects of interventions that ensure maximum greenness exposure versus minimum through all intervals; and that ensure maximum greenness only in early childhood (vs. minimum through all intervals). Results of the effects of "maximum (vs. minimum) greenness at all timepoints" did not suggest associations with mid-childhood outcomes. Estimates of "maximum greenness only in early childhood (vs. minimum)" suggested a beneficial association with mid-childhood SDQ (-3.21, 99 %CI: -6.71,0.29 mother-rated; -4.02, 99 %CI: -7.87,-0.17 teacher-rated). No associations were observed with early adolescent outcomes. Our results for "persistent" maximum greenness exposure on behavior, were not conclusive with confidence intervals containing the null. The results for maximum greenness "only in early childhood" may shed light on sensitive periods of greenness exposure for behavior regulation.

Indexed as

EnvironmentExecutive FunctionAdolescentChildChild, PreschoolHumansInfant, NewbornModels, StructuralProbabilityChildren's healthExecutive functionGreen spaceInverse probability weightingSensitive periods

Identifiers

PMID34740291
PMCPMC9208930

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.