Evidence map›Paper›PMID 38681766›Full record

ArticleFrontiers in endocrinology2024

Global trends and spatial drivers of diabetes mellitus mortality, 1990-2019: a systematic geographical analysis.

Zejia Xu, Jianheng Feng, Siyi Xing, Yin Liu, Yuting Chen, Jie Li, Yunhui Feng

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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

7 authors.

Zejia XuSchool of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China.
Jianheng FengFaculty of Innovation and Design, City University of Macau, Macao, Macao SAR, China.
Siyi XingSchool of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China.
Yin LiuSchool of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China.
Yuting ChenSchool of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China.
Jie LiSchool of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China.
Yunhui FengCenter for Interdisciplinary Health Management Studies, School of Physical Education & Sports Science, Guangzhou University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Diabetes mellitus is the leading cause of death worldwide, and multiple risk factors associated with diabetes mortality. Methods: Employing spatial statistics, we characterized the spatial distribution and patterns of diabetes mortality, and revealed the spatial relationship between diabetes mortality and 11 socioeconomic and environmental risk factors at the country level, from 1990 to 2019. Results: Globally, significantly high rates of diabetes mortality were primarily clustered in countries with limited land areas or located on islands, such as Fiji, Kiribati, Eswatini, and Trinidad and Tobago. Countries with weaker economic independence are more likely to have higher diabetes mortality rates. In addition, the impact of socioeconomic and environmental factors was significant at the country level, involving health expenditure, number of physicians, household and ambient air pollution, smoking, and alcohol consumption. Notably, the spatial relationship between diabetes mortality and ambient air pollution, as well as alcohol consumption, showed negative correlations. Countries with high diabetes mortality rates generally had lower levels of ambient air pollution and alcohol consumption. Conclusion: The study highlights the spatial clustering of diabetes mortality and its substantial variation. While many risk factors can influence diabetes mortality, it's also essential to consider the level of these factors at the country level. Tailoring appropriate interventions based on specific national circumstances holds the potential to more effectively mitigate the burden of diabetes mortality.

Indexed as

Diabetes MellitusGlobal HealthSpatial AnalysisAir PollutionHumansMortalityRisk FactorsSocioeconomic Factorsdiabetesrisk factorspatial regressionspatiotemporal variationsustainable development goals

Identifiers

PMID38681766
PMCPMC11045957

What OpenQuestion holds

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Registered trials

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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.