Evidence map›Paper›PMID 34395689›Full record

ArticleAIMS public health2021

A cross-sectional population-based study on the influence of the COVID-19 pandemic on incomes in Greece.

Dimitris Zavras

Open access · goldAbstract read
In one paragraph

Article in AIMS public health, 2021. 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
2.1field-weighted citation impact, top 9% of its field
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, 7 citations in OpenAlex.

  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

1 author at 1 institution in 1 country.

Dimitris ZavrasDepartment of Public Health Policy, School of Public Health, University of West Attica, Athens, Greece.
University of West Attica · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Coronavirus Disease 2019 (COVID-19) pandemic induced economic shock in Greece, which translated into a decrease in household income. Thus, the objective of this study is to measure social inequality with regard to income loss due to the COVID-19 pandemic in Greece. In addition, we aim to identify the characteristics of those experiencing income loss due to the pandemic. The study uses data from the "Public Opinion in the European Union (EU) in Time of Coronavirus Crisis. Third Round" survey. The sample consists of 1036 individuals aged between 16 and 54 years. To measure inequality, the Erreygers' Concentration Index (CI) is calculated, using social class as the ranking variable. To identify the characteristics of those experiencing income loss, a logistic regression model is fitted using the region of residence and several demographic and socioeconomic variables as potential predictors. According to the results, social inequality does not exist with regard to income loss due to the COVID-19 pandemic. Thus, our findings indicate the negative influence of the pandemic on the incomes of individuals from all social classes in Greece. According to the results of the logistic regression model, the odds of experiencing income loss are higher for residents of the Aegean Islands and Crete but also for self-employed, part-time employed, and unemployed individuals. These findings indicate the negative influence of the pandemic on Greek tourism and on sectors employing a large proportion of non-standard workers. Although inequality does not exist, a substantial proportion of those losing income due to the pandemic is in line with the global picture.

Indexed as

COVID-19employment statusgeographic regionloss of incomesocial inequalitytourism

Identifiers

PMID34395689
PMCPMC8334635
OpenAlexW3159130197

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.