Evidence map›Paper›PMID 40426138›Full record

SynthesisBMC public health2025

Gini coefficient, GDP per capita and COVID-19 mortality: a systematic review of ecologic studies.

Amir Farhang Abbasi, Negin Karimi Dehkordi, Neda SoleimanvandiAzar, Mahshid Roohravan Benis, Marzieh Nojomi

Abstract readSystematic Review
In one paragraph

Synthesis in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Amir Farhang AbbasiStudent Research Committee, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0002-4905-649X
Negin Karimi DehkordiStudent Research Committee, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0002-4432-5881
Neda SoleimanvandiAzarPreventive Medicine and Public Health Research Center, Psychosocial Health Research Institute, Department of Community and Family Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0002-9840-5588
Mahshid Roohravan BenisPreventive Medicine and Public Health Research Center, Psychosocial Health Research Institute, Department of Community and Family Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0009-0009-2915-3725
Marzieh NojomiPreventive Medicine and Public Health Research Center, Psychosocial Health Research Institute, Department of Community and Family Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Iran. mnojomi@iums.ac.ir.ORCID http://orcid.org/0000-0003-4330-3522

Funding

Iran University of Medical Sciences 1401-4-90-24758
6 · The paper itself

Abstract

backgroundSince December 2019, when Wuhan officially reported COVID-19, the disease has spread globally, revealing significant variations in mortality rates influenced by socio-economic factors and health policies. This study aims to identify two predictors of COVID-19 mortality differences-GDP (Gross Domestic Product), and Gini Coefficient index-across various countries through a systematic review.

methodsThe study was a systematic review conducted according to PRISMA guidelines. The search strategy was searched in the titles and abstracts of the articles in three main databases: PubMed, Scopus, and Web of Science. Gini Coefficients and the Gross Domestic Product (GDP) of the countries were used as mortality predictors. The initial search yielded 331 articles, which were assessed for quality using the Newcastle Ottawa Scale (NOS). Ultimately, 31 articles were included in the final synthesis.

resultsMost studies analyzed data from multiple countries, with only ten of the thirty-one articles focusing on a single nation. Initial research in 2020 aimed to understand the immediate socioeconomic factors affecting COVID-19 outcomes. Later studies in 2021 and 2022 explored more complex interactions between the pandemic and socioeconomic factors, while long-term outcomes were published in 2023 and 2024. Some studies found a paradoxical relationship between GDP and COVID-19 mortality rates, whereas most indicated a positive correlation between COVID-19 mortality rates and the Gini index.

conclusionBoth income inequality and GDP significantly influence COVID-19 mortality rates. While a higher GDP can provide some protective benefits, it does not completely shield countries from high mortality, especially when considering economic activity and demographics. Researchers consistently identify income inequality as a predictor of poorer health outcomes, highlighting the need for equitable health and social policies to mitigate vulnerabilities in future pandemics.

Indexed as

COVID-19Gross Domestic ProductGlobal HealthHumansSARS-CoV-2Socioeconomic FactorsCOVID-19Gini coefficientGross Domestic Product (GDP)Mortality Rate

Identifiers

PMID40426138
PMCPMC12107963

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.