Evidence map›Paper›PMID 33919144›Full record

ArticleInternational journal of environmental research and public health2021

Importance of Geospatial Heterogeneity in Chronic Disease Burden for Policy Planning in an Urban Setting Using a Case Study of Singapore.

Ken Wei Tan, Joel R Koo, Jue Tao Lim, Alex R Cook, Borame L Dickens

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Ken Wei TanSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore 117549, Singapore.
Joel R KooSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore 117549, Singapore.
Jue Tao LimSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore 117549, Singapore.
Alex R CookSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore 117549, Singapore.
Borame L DickensSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore 117549, Singapore.ORCID 0000-0003-1592-1745

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic disease burdens continue to rise in highly dense urban environments where clustering of type II diabetes mellitus, acute myocardial infarction, stroke, or any combination of these three conditions is occurring. Many individuals suffering from these conditions will require longer-term care and access to clinics which specialize in managing their illness. With Singapore as a case study, we utilized census data in an agent-modeling approach at an individual level to estimate prevalence in 2020 and found high-risk clusters with >14,000 type II diabetes mellitus cases and 2000-2500 estimated stroke cases. For comorbidities, 10% of those with type II diabetes mellitus had a past acute myocardial infarction episode, while 6% had a past stroke. The western region of Singapore had the highest number of high-risk individuals at 173,000 with at least one chronic condition, followed by the east at 169,000 and the north with the least at 137,000. Such estimates can assist in healthcare resource planning, which requires these spatial distributions for evidence-based policymaking and to investigate why such heterogeneities exist. The methodologies presented can be utilized within any urban setting where census data exists.

Indexed as

Diabetes Mellitus, Type 2Chronic DiseaseCost of IllnessHumansPolicySingaporechronic diseaseenvironmental healthspatial epidemiologystatistical modelingurbanization

Identifiers

PMID33919144
PMCPMC8122641

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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.