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Dataset on cigarette smokers in six South African townships

A total of 2453 smokers were interviewed in townships over two rounds of data collection. Townships are low-income, urban areas characterised by overpopulation, poor service delivery, crime, and poor socioeconomic outcomes. Township residents typically live in poverty. Data were collected from six t...

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Autores principales: Vellios, Nicole, van der Zee, Kirsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7490728/
https://www.ncbi.nlm.nih.gov/pubmed/32964081
http://dx.doi.org/10.1016/j.dib.2020.106260
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author Vellios, Nicole
van der Zee, Kirsten
author_facet Vellios, Nicole
van der Zee, Kirsten
author_sort Vellios, Nicole
collection PubMed
description A total of 2453 smokers were interviewed in townships over two rounds of data collection. Townships are low-income, urban areas characterised by overpopulation, poor service delivery, crime, and poor socioeconomic outcomes. Township residents typically live in poverty. Data were collected from six townships in four of South Africa's nine provinces, namely Gauteng (Eldorado Park and Ivory Park), Western Cape (Khayelitsha and Mitchell's Plain), Free State (Thabong) and KwaZulu-Natal (Umlazi). These townships were chosen to represent both the geographical and racial spread of low socioeconomic areas in South Africa. Round 1 data (n = 1260) were collected from October to November 2017, and round 2 data (n = 1193) were collected from July to August 2018. The sample includes two of South Africa's four population groups: African and mixed race (locally referred to as “Coloured”, which describes people of mixed Khoisan, Malay, European, and black African ancestry). Since few Whites and Asians live in townships, they were not sampled. Households were selected via a random walk through each township. One smoker per household was interviewed (if a household contained at least one available smoker). We aimed to interview 200 adult smokers (aged 18+ years) per township per round. If a household had more than one smoker, a random selection determined which smoker to interview. Respondents were asked about their most recent cigarette purchase, specifically packaging type (single stick, pack, or carton), number of items purchased, brand, type of outlet where the cigarettes were bought, and the total amount paid for cigarettes. Respondents were also asked about other tobacco use in the household, and about their perceptions regarding illegal cigarettes. Socioeconomic and demographic information was collected at the individual and household level. The data has been used to estimate illicit trade (https://tobaccocontrol.bmj.com/content/early/2020/03/10/tobaccocontrol-2019–055136.info), and to analyse the determinants of smoking intensity (https://www.sciencedirect.com/science/article/pii/S2211335520300590).
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spelling pubmed-74907282020-09-21 Dataset on cigarette smokers in six South African townships Vellios, Nicole van der Zee, Kirsten Data Brief Data Article A total of 2453 smokers were interviewed in townships over two rounds of data collection. Townships are low-income, urban areas characterised by overpopulation, poor service delivery, crime, and poor socioeconomic outcomes. Township residents typically live in poverty. Data were collected from six townships in four of South Africa's nine provinces, namely Gauteng (Eldorado Park and Ivory Park), Western Cape (Khayelitsha and Mitchell's Plain), Free State (Thabong) and KwaZulu-Natal (Umlazi). These townships were chosen to represent both the geographical and racial spread of low socioeconomic areas in South Africa. Round 1 data (n = 1260) were collected from October to November 2017, and round 2 data (n = 1193) were collected from July to August 2018. The sample includes two of South Africa's four population groups: African and mixed race (locally referred to as “Coloured”, which describes people of mixed Khoisan, Malay, European, and black African ancestry). Since few Whites and Asians live in townships, they were not sampled. Households were selected via a random walk through each township. One smoker per household was interviewed (if a household contained at least one available smoker). We aimed to interview 200 adult smokers (aged 18+ years) per township per round. If a household had more than one smoker, a random selection determined which smoker to interview. Respondents were asked about their most recent cigarette purchase, specifically packaging type (single stick, pack, or carton), number of items purchased, brand, type of outlet where the cigarettes were bought, and the total amount paid for cigarettes. Respondents were also asked about other tobacco use in the household, and about their perceptions regarding illegal cigarettes. Socioeconomic and demographic information was collected at the individual and household level. The data has been used to estimate illicit trade (https://tobaccocontrol.bmj.com/content/early/2020/03/10/tobaccocontrol-2019–055136.info), and to analyse the determinants of smoking intensity (https://www.sciencedirect.com/science/article/pii/S2211335520300590). Elsevier 2020-09-02 /pmc/articles/PMC7490728/ /pubmed/32964081 http://dx.doi.org/10.1016/j.dib.2020.106260 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Vellios, Nicole
van der Zee, Kirsten
Dataset on cigarette smokers in six South African townships
title Dataset on cigarette smokers in six South African townships
title_full Dataset on cigarette smokers in six South African townships
title_fullStr Dataset on cigarette smokers in six South African townships
title_full_unstemmed Dataset on cigarette smokers in six South African townships
title_short Dataset on cigarette smokers in six South African townships
title_sort dataset on cigarette smokers in six south african townships
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7490728/
https://www.ncbi.nlm.nih.gov/pubmed/32964081
http://dx.doi.org/10.1016/j.dib.2020.106260
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