Evidence map›Paper›PMID 35760115›Full record

ArticleEnvironmental research2022

Street-view greenspace exposure and objective sleep characteristics among children.

Marcia P Jimenez, Esra Suel, Sheryl L Rifas-Shiman, Perry Hystad, Andrew Larkin, Steve Hankey, Allan C Just, Susan Redline, Emily Oken, Peter James and 1 more

Open access · greenAbstract read
In one paragraph

Article in Environmental research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% of its field
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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Advancing Social and Environmental Research in Cancer Registries Using Geomasking for Address-Level Data.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

11 authors at 7 institutions in 2 countries.

Marcia P JimenezDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA. Electronic address: jimenezm@bu.edu.
Esra SuelFaculty of Medicine, School of Public Health, Imperial College London, London, UK.
Sheryl L 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.
Perry HystadCollege of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA.
Andrew LarkinCollege of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA.
Steve HankeySchool of Public and International Affairs, Virginia Tech University, Blacksburg, VA, USA.
Allan C JustDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Susan RedlineBrigham and Women's Faulkner Hospital, Sleep Medicine and Endocrinology Center, Boston, MA, USA.
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.
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.
See Acknowledgments for full listing of collaborators
Harvard University · USOregon State University · USBoston University · USBrigham and Women's Faulkner Hospital · USIcahn School of Medicine at Mount Sinai · USImperial College London · GBVirginia Tech · US

Funding

Project-005U2COD023375 · OD · DUKE UNIVERSITY · PI Linda S Adair, Phillip Brian Smith · 2016 to 2026
$215.9M
ECHODAC (Environmental Influences on Child Health Outcomes Data Analysis Center)U24OD023382 · OD · JOHNS HOPKINS UNIVERSITY · PI Diane J Catellier, LISA P JACOBSON · 2016 to 2026
$148.4M
The ECHO Measurement Core: A Framework and Resource for Assessing Environmental Exposure and Child HealthU24OD023319 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Courtney K Blackwell, RICHARD GERSHON · 2016 to 2026
$43.7M
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
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
Medical Research Council MR/S003983/1NCI NIH HHS R00 CA201542NHLBI NIH HHS R01 HL150119NIA NIH HHS K99 AG066949NIA NIH HHS R00 AG066949NICHD NIH HHS R01 HD034568NIH HHS U24 OD023319NIH HHS U24 OD023382NIH HHS U2C OD023375NIH HHS UH3 OD023286
6 · The paper itself

Abstract

Greenspace may benefit sleep by enhancing physical activity, reducing stress or air pollution exposure. Studies on greenspace and children's sleep are limited, and most use satellite-derived measures that do not capture ground-level exposures that may be important for sleep. We examined associations of street view imagery (SVI)-based greenspace with sleep in Project Viva, a Massachusetts pre-birth cohort. We used deep learning algorithms to derive novel metrics of greenspace (e.g., %trees, %grass) from SVI within 250m of participant residential addresses during 2007-2010 (mid-childhood, mean age 7.9 years) and 2012-2016 (early adolescence, 13.2y) (N = 533). In early adolescence, participants completed >5 days of wrist actigraphy. Sleep duration, efficiency, and time awake after sleep onset (WASO) were derived from actigraph data. We used linear regression to examine cross-sectional and prospective associations of mid-childhood and early adolescence greenspace exposure with early adolescence sleep, adjusting for confounders. We compared associations with satellite-based greenspace (Normalized Difference Vegetation Index, NDVI). In unadjusted models, mid-childhood SVI-based total greenspace and %trees (per interquartile range) were associated with longer sleep duration at early adolescence (9.4 min/day; 95%CI:3.2,15.7; 8.1; 95%CI:1.7,14.6 respectively). However, in fully adjusted models, only the association between %grass at mid-childhood and WASO was observed (4.1; 95%CI:0.2,7.9). No associations were observed between greenspace and sleep efficiency, nor in cross-sectional early adolescence models. The association between greenspace and sleep differed by racial and socioeconomic subgroups. For example, among Black participants, higher NDVI was associated with better sleep, in neighborhoods with low socio-economic status (SES), higher %grass was associated with worse sleep, and in neighborhoods with high SES, higher total greenspace and %grass were associated with better sleep time. SVI metrics may have the potential to identify specific features of greenspace that affect sleep.

Indexed as

Air PollutionParks, RecreationalAdolescentChildCross-Sectional StudiesHumansResidence CharacteristicsSleepTreesChildren's healthDeep learning algorithmsEnvironmental epidemiologyGreenspaceLongitudinal dataSleep

Identifiers

PMID35760115
PMCPMC9930007
OpenAlexW4283457256

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.