Evidence map›Paper›PMID 28484362›Full record

ArticleTobacco induced diseases2017

Socio-demographic characteristics and tobacco use among the adults in urban slums of Dhaka, Bangladesh.

Nusrat Nausheen Khandker, Tuhin Biswas, Abdullah Nurus Salam Khan, Enamul Hasib, Lal B Rawal

Abstract read
In one paragraph

Article in Tobacco induced diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 citing papers in PubMed.

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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

5 authors.

Nusrat Nausheen KhandkerJames P Grant School of Public Health, BRAC University, Dhaka, Bangladesh.
Tuhin BiswasHealth Systems and Population Studies Division, icddr, b Level 5, 68 Shaheed Tajuddin Ahmed Sharani, Mohakhali, Dhaka, 1212 Bangladesh.
Abdullah Nurus Salam KhanHealth Systems and Population Studies Division, icddr, b Level 5, 68 Shaheed Tajuddin Ahmed Sharani, Mohakhali, Dhaka, 1212 Bangladesh.
Enamul HasibJames P Grant School of Public Health, BRAC University, Dhaka, Bangladesh.
Lal B RawalJames P Grant School of Public Health, BRAC University, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUse of tobacco has become one of the major causes of premature deaths in most developing countries, including Bangladesh. The poorest and most disadvantaged populations, such as those living in slums, are considered to be extremely vulnerable to non-communicable diseases and their risk factors, especially tobacco use. The objective of this study was to assess the current status of tobacco consumption among slum dwellers and its association with socio-demographic factors.

methodsA cross-sectional study was conducted in three slums of Dhaka city. Information about tobacco use as well as socio-demographic characteristics was collected from adult slum dwellers via face to face interviews using WHO STEPS questionnaire.

resultOverall proportion of smoking, smokeless tobacco consumption and dual use of tobacco was 35% [95% CI: 31.6-39.8], 40.6% [95% CI: 36.5-45.2] and 12% [95% CI: 9.3-15.0] respectively. Elderly people (55-64 years) were more likely to smoke (OR: 2.34, 95% CI: 1.21-4.49) than younger people (aged 25-34 years). On the other hand, those who had no schooling history (OR: 2.95, 95% CI: 1.66-5.25) were more likely to consume smokeless tobacco than those who had higher education (secondary or above). At the same time, manual workers were more likely to indulge in dual use of tobacco (OR: 5.17, 95% CI: 2.82-9.48) as compared to non-manual workers.

conclusionThe urban slum population of Dhaka city has a high prevalence of tobacco use, which increases their likelihood of developing non-communicable diseases. Proper attention needs to be directed towards addressing the risk factors related to non-communicable diseases within this vulnerable population.

Indexed as

BangladeshDhakaTobacco useUrban slum

Identifiers

PMID28484362
PMCPMC5420145

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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.