A2 Refereed review article in a scientific journal
Tobacco retailer density and smoking behaviour: how are exposure and outcome measures classified? A systematic review
Authors: Baker John, Lenz Katrin, Masood Mohd, Rahman Muhammad Aziz, Begg Stephen
Publication year: 2023
Journal: BMC Public Health
Journal name in source: BMC PUBLIC HEALTH
Article number: 2038
Volume: 23
Issue: 1
eISSN: 1471-2458
DOI: https://doi.org/10.1186/s12889-023-16914-y
Web address : https://doi.org/10.1186/s12889-023-16914-y
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/181908717
Introduction
To date only a limited number of reviews have focused on how exposure and outcome measures are defined in the existing literature on associations between tobacco retailer density (‘density’) and smoking behaviour (‘smoking’). Therefore this systematic review classified and summarised how both density and smoking variables are operationalised in the existing literature, and provides several methodological recommendations for future density and smoking research.
MethodsTwo literature searches between March and April 2018 and April 2022 were conducted across 10 databases. Inclusion and exclusion criteria were developed and keyword database searches were undertaken. Studies were imported into Covidence. Cross-sectional studies that met the inclusion criteria were extracted and a quality assessment was undertaken. Studies were categorised according to the density measure used, and smoking was re-categorised using a modified classification tool.
ResultsLarge heterogeneity was found in the operationalisation of both measures in the 47 studies included for analysis. Density was most commonly measured directly from geocoded locations using circular buffers at various distances (n = 14). After smoking was reclassified using a smoking classification tool, past-month smoking was the most common smoking type reported (n = 26).
ConclusionsIt is recommended that density is measured through length-distance and travel time using the street network and weighted (e.g. by the size of an area), or by using Kernel Density Estimates as these methods provide a more accurate measure of geographical to tobacco and e-cigarette retailer density. The consistent application of a smoking measures classification tool, such as the one developed for this systematic review, would enable better comparisons between studies. Future research should measure exposure and outcome measures in a way that makes them comparable with other studies.
ImplicationsDownloadable publication This is an electronic reprint of the original article. |