Evidence map›Paper›PMID 36754963›Full record

ArticleScientific data2023

Gridded Datasets for Japan: Total, Male, and Female Populations from 2001-2020.

Chao Li, Shunsuke Managi

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. The use of public spatial databases in risk analysis: A US-oriented tutorial.Risk analysis : an official publication of the Society for Risk Analysis · 2025
    Article
  3. 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

2 authors.

Chao LiUrban Institute & School of Engineering, Kyushu University, Fukuoka, Japan.
Shunsuke ManagiUrban Institute & School of Engineering, Kyushu University, Fukuoka, Japan. managi@doc.kyushu-u.ac.jp.ORCID 0000-0001-7883-1427

Funding

MEXT | Japan Society for the Promotion of Science (JSPS) JP20H00648
6 · The paper itself

Abstract

Japan is a highly urbanized and severely aging society. In an aging society, chronic disease and disability are prevalent, and the population is sensitive to environmental issues and climate change. To identify the effects of population changes, formulate population and public health policies, and assist environmental projects, a high-resolution and accurate gridded population dataset is highly desirable. To provide basic data for research in these areas, we created an open access annual dataset from 2001 to 2020 containing the total, male, and female population counts in each grid at a resolution of 500 m. A random forest method was employed to fill the gaps in Japan's nationwide census data collected in 2005, 2010, 2015, and 2020. The yearly population dataset was based on the 4

Indexed as

CensusesSex DistributionFemaleHumansJapanMale

Identifiers

PMID36754963
PMCPMC9908984

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.