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Smoking behaviours and indoor air quality: a comparative analysis of smoking-permitted versus smoke-free homes in Dhaka, Bangladesh
  1. Tarana Ferdous1,
  2. Kamran Siddiqi2,
  3. Sean Semple3,
  4. Caroline Fairhurst4,
  5. Ruaraidh Dobson5,
  6. Noreen Mdege2,
  7. Anna-Marie Marshall2,
  8. S M Abdullah6,7,
  9. Rumana Huque6,7
  1. 1 Epidemiology research, ARK Foundation, Dhaka, Bangladesh
  2. 2 Institute of Health Sciences, University of York, York, North Yorkshire, UK
  3. 3 Institute of Social Marketing, University of Stirling Institute for Social Marketing, Stirling, UK
  4. 4 York Trials Unit, Department of Health Sciences, University of York, York, North Yorkshire, UK
  5. 5 G10 Pathfoot Building Stirling Campus, University of Stirling Institute for Social Marketing, Stirling, UK
  6. 6 Economics, University of Dhaka, Dhaka, Dhaka District, Bangladesh
  7. 7 Health Economics research, ARK Foundation, Dhaka, Bangladesh
  1. Correspondence to Tarana Ferdous, Epidemiology, ARK Foundation, Dhaka 1212, Bangladesh; tarana{at}arkfoundationbd.org

Abstract

Introduction Exposure to secondhand smoke (SHS) is a health risk to non-smokers. Indoor particulate matter (PM2.5) is associated with SHS exposure and is used as a proxy measure. However, PM2.5 is non-specific and influenced by a number of environmental factors, which are subject to geographical variation. The nature of association between SHS exposure and indoor PM2.5—studied primarily in high-income countries (HICs) context—may not be globally applicable. We set out to explore this association in a low/middle-income country setting, Dhaka, Bangladesh.

Methods A cross-sectional study was conducted among households with at least one resident smoker. We inquired whether smoking was permitted inside the home (smoking-permitted homes, SPH) or not (smoke-free homes, SFH), and measured indoor PM2.5 concentrations using a low-cost instrument (Dylos DC1700) for at least 22 hours. We describe and compare SPH and SFH and use multiple linear regression to evaluate which variables are associated with PM2.5 level among all households.

Results We surveyed 1746 households between April and August 2018; 967 (55%) were SPH and 779 (45%) were SFH. The difference between PM2.5 values for SFH (median 27 µg/m3, IQR 25) and SPH (median 32 µg/m3, IQR 31) was 5 µg/m3 (p<0.001). Lead participant’s education level, being a non-smoker, having outdoor space and smoke-free rule at home and not using kerosene oil for cooking were significantly associated with lower PM2.5.

Conclusions We found a small but significant difference between PM2.5 concentrations in SPH compared with SFH in Dhaka, Bangladesh—a value much lower than observed in HICs.

  • low/middle income country
  • secondhand smoke
  • environment
  • global health
  • socioeconomic status

Data availability statement

Data are available upon reasonable request. The data used in this study are the baseline data of a cluster randomised controlled trial (cRCT) study. The protocol manuscript link is given below https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-018-3100-y. The final analysis of the post-intervention data is ongoing. Data could be made available upon reasonable request after completion of all intended publication of this trial. It would be best to contact the trial chief PI (Siddiqi, Kamran, email: kamran.siddiqi@york.ac.ukORCiD ID: 0000-0003-1529-7778) for further queries.

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Data availability statement

Data are available upon reasonable request. The data used in this study are the baseline data of a cluster randomised controlled trial (cRCT) study. The protocol manuscript link is given below https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-018-3100-y. The final analysis of the post-intervention data is ongoing. Data could be made available upon reasonable request after completion of all intended publication of this trial. It would be best to contact the trial chief PI (Siddiqi, Kamran, email: kamran.siddiqi@york.ac.ukORCiD ID: 0000-0003-1529-7778) for further queries.

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Footnotes

  • Twitter @TaranaFT

  • Contributors TF cooridinated the study data collection and management, prepared the manuscript, developed the analytical strategy, contributed to the statistical analysis and interpretation of the results, and wrote the first draft of the report. KS and RH conceptualised the study. SS led the design of obtaining PM2.5 measurements. CF, RD and SMA contributed to statistical analysis and interpretation of the results. NM and A-MM contributed to the interpretation of results and revision of the report. All authors participated in manuscript revisions, and read and approved the final manuscript.

  • Funding This work was supported by the ‘Medical Research Council’ (grant number MR/P008941/1).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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