Evidence map›Paper›PMID 36429792›Full record

ArticleInternational journal of environmental research and public health2022

Green Space Exposure and Obesity in the Mexican Adult Population.

Nabetse Baruc Blas-Miranda, Ana Lilia Lozada-Tequeanes, Juan Antonio Miranda-Zuñiga, Marcia P Jimenez

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 22% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

4 authors at 3 institutions in 2 countries.

Nabetse Baruc Blas-MirandaNutrition and Health Research Center (CINyS), National Institute of Public Health of Mexico (INSP), Cuernavaca 62100, Mexico.ORCID 0000-0002-7559-8452
Ana Lilia Lozada-TequeanesNutrition and Health Research Center (CINyS), National Institute of Public Health of Mexico (INSP), Cuernavaca 62100, Mexico.ORCID 0000-0002-7371-3525
Juan Antonio Miranda-ZuñigaDepartment of Actuarial Science, National Autonomous University of Mexico (UNAM), Mexico City 04510, Mexico.ORCID 0000-0002-5975-1517
Marcia P JimenezDepartment of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA.ORCID 0000-0001-5240-7898
Instituto Nacional de Salud Pública · MXBoston University · USUniversidad Nacional Autónoma de México · MX

Funding

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
NIA NIH HHS R00 AG066949
6 · The paper itself

Abstract

Green space or natural vegetation may reduce obesity risk by increasing opportunities for physical activity or reducing stress and exposure to other pollutants. Obesity prevalence in Mexico is ranked among the highest in the world. However, research on the association between green space and obesity in Mexico is lacking. We used data from the National Nutrition Survey in Mexico (2018-2019), a nationally representative sample of Mexican adults. The analytical sample included participants between 20-59 years of age (

Indexed as

ObesityParks, RecreationalAdultBody Mass IndexExerciseHumansMexicoenvironmental healthgreen spaceLatino populationobesityspatial epidemiology

Identifiers

PMID36429792
PMCPMC9690096
OpenAlexW4309118430

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.