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Spat Spatiotemporal Epidemiol. 2015 Jan;12:1-7. doi: 10.1016/j.sste.2014.09.001. Epub 2014 Oct 5.

The association between the density of retail tobacco outlets, individual smoking status, neighbourhood socioeconomic status and school locations in New South Wales, Australia.

Author information

1
Centre for Epidemiology and Evidence, NSW Ministry of Health, Locked Mail Bag 961, North Sydney NSW, 2059, Australia. Electronic address: Sadaf.MarashiPour@health.nsw.gov.au.
2
Public Health Intelligence Branch, Centre for Epidemiology and Evidence, NSW Ministry of Health, Locked Mail Bag 961, North Sydney NSW, 2059, Australia. Electronic address: mcret@doh.health.nsw.gov.au.
3
Strategy and Partnerships Branch, Centre for Population Health, NSW Ministry of Health, Locked Mail Bag 961, North Sydney NSW, 2059, Australia. Electronic address: Claudine.lyons@doh.health.nsw.gov.au.
4
Public Health Intelligence Branch, Centre for Epidemiology and Evidence, NSW Ministry of Health, Locked Mail Bag 961, North Sydney NSW, 2059, Australia. Electronic address: nrose@doh.health.nsw.gov.au.
5
Centre for Research, Evidence Management and Surveillance, South Western Sydney and Sydney Local Health Districts, Locked Bag 7017, Liverpool, NSW, 1871, Australia; School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia. Electronic address: bin.jalaludin@sswahs.nsw.gov.au.
6
Centre for Population Health, NSW Ministry of Health, Locked Mail Bag 961, North Sydney NSW, 2059, Australia. Electronic address: Joanne.smith@iinet.net.au.

Abstract

AIM:

We explored the association between the density of tobacco outlets and neighbourhood socioeconomic status, and between neighbourhood tobacco outlet density and individual smoking status. We also investigated the density of tobacco outlets around primary and secondary schools in New South Wales (NSW).

METHODS:

We calculated the mean density of retail tobacco outlets registered in NSW between 2009 and 2011, using kernel density estimation with an adaptive bandwidth. We used generalised ordered logistic regression model to explore the association between socioeconomic status and density of tobacco outlets. The association between neighbourhood tobacco outlet density and individuals' current smoking status was investigated using random-intercept generalised linear mixed models. We also calculated the median tobacco outlet density around NSW schools.

RESULTS:

More disadvantaged Census Collection Districts (CDs) were significantly more likely to have higher tobacco outlet densities. After adjusting for neighbourhood socioeconomic status and participants' age, sex, country of birth and Aboriginal status, neighbourhood mean tobacco outlet density was significantly and positively associated with individuals' smoking status. The median of tobacco outlet density around schools was significantly higher than the state median.

CONCLUSION:

Policymakers could consider exploring a range of strategies that target tobacco outlets in proximity to schools, in more disadvantaged neighbourhoods and in areas of existing high tobacco outlet density.

KEYWORDS:

Generalised ordered logistic regression; Kernel density; Smoking; Socio-economic status; Tobacco outlet density

PMID:
25779904
DOI:
10.1016/j.sste.2014.09.001
[Indexed for MEDLINE]

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