Evidence map›Paper›PMID 34222728›Full record

ArticleTobacco prevention & cessation2021

Socioeconomic status and tobacco consumption: Analyzing inequalities in China, Ghana, India, Mexico, the Russian Federation and South Africa.

Laura Rossouw

Open access · goldAbstract read
In one paragraph

Article in Tobacco prevention & cessation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 7% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
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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.

Laura RossouwSchool of Economics and Finance, University of the Witwatersrand, Johannesburg, South Africa.
University of the Witwatersrand · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGlobally, there has been a rapid rise in non-communicable diseases driven by changing lifestyle choices and health behaviors. Different lifestyle choices threaten to exacerbate existing health inequalities, yet evidence monitoring the extent of this impact in emerging economies is lacking. The article sets out to measure the level of wealth-related inequality and its drivers in one of these lifestyle choices, tobacco consumption, among populations aged ≥50 years in six Low- and Middle-Income Countries.

methodsThe study provides empirical evidence of the inequality in tobacco consumption across wealth groups in China, Ghana, India, Mexico, the Russian Federation and South Africa using the Erreygers' corrected concentration indices. These inequalities are then decomposed to gain a deeper understanding of the factors and broader social forces driving inequality. The WHO SAGE data set, collected between 2008 and 2010, is used for the analysis.

resultsCurrent tobacco consumption is concentrated among the poor in China, Ghana, India, and South Africa, and among the wealthy in the Russian Federation and Mexico. The inequalities widen when we focus solely on the male population. Although the results differ by country, the major drivers of inequality include wealth, locality, and gender.

conclusionsThe focus on tobacco consumption in this age group is key to curbing rising healthcare costs and ensuring longevity. Policies aimed at reducing wealth-related inequalities should especially target high tobacco consumption rates among males, while simultaneously pre-empting and curbing rising rates among women.

Indexed as

inequalityLMICnon-communicable diseasesSEStobaccotobacco control

Identifiers

PMID34222728
PMCPMC8231441
OpenAlexW3175489718

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.