Evidence map›Paper›PMID 34762746›Full record

ArticleThe International journal of health planning and management2022

Demography, inequalities and Global Health Security Index as correlates of COVID-19 morbidity and mortality.

Seda Kumru, Pakize Yiğit, Osman Hayran

Abstract read
In one paragraph

Article in The International journal of health planning and management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

3 authors.

Seda KumruHealth Management Department, Faculty of Health Sciences, Izmir Bakircay University, Izmir, Turkey.ORCID https://orcid.org/0000-0001-7083-1377
Pakize YiğitDepartment of Medical Statistics and Medical Informatics, Medical School, Istanbul Medipol University, Istanbul, Turkey.ORCID https://orcid.org/0000-0002-5919-1986
Osman HayranDepartment of Public Health, Medical School, Istanbul Medipol University, Istanbul, Turkey.ORCID https://orcid.org/0000-0002-9994-5033

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring a pandemic, the occurrence of infections and case fatality rates are expected to vary from one country to another due to several variables such as poverty, existing comorbidities, population density, access to health care, availability and quality of health system resources, and environmental factors.

objectivesOur aim is to investigate the relationship between various demographic and socioeconomic factors and reported COVID-19 morbidity and mortality indicators in different countries. Also, to determine the position of the countries relative to each other in terms of three indicators including COVID-19 cases, deaths and tests.

methodsCanonical correlation analysis is used to investigate the intercorrelations between independent variables and the COVID-19 cases and deaths for 92 countries. Countries' performances are measured by MULTIMOORA.

resultsHuman Development Index, smoking habits, percentage of elderly population and test frequency are the most significant variables associated with COVID-19 morbidity and mortality according to our study findings. Singapore, New Zealand and Australia are the best performed countries.

conclusionsSeveral significant and unexpected associations exist between socioeconomic factors and the COVID-19 cases and deaths. Singapore, New Zealand and Australia are surrounded by water, have been more successful in the pandemic process compared to other countries.

Indexed as

COVID-19AgedGlobal HealthHumansMorbidityMortalityPopulation DensitySARS-CoV-2COVID-19 pandemicdemographyhealth policysocioeconomic factors

Identifiers

PMID34762746
PMCPMC8652976

What OpenQuestion holds

Textmetadata
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.