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Mapping Cigarettes Similarities using Cluster Analysis Methods

The aim of the research was to investigate the relationship and/or occurrences in and between chemical composition information (tar, nicotine, carbon monoxide), market information (brand, manufacturer, price), and public health information (class, health warning) as well as clustering of a sample of...

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Detalles Bibliográficos
Autores principales: Bolboacă, Sorana D., Jäntschi, Lorentz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3731640/
https://www.ncbi.nlm.nih.gov/pubmed/17911663
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author Bolboacă, Sorana D.
Jäntschi, Lorentz
author_facet Bolboacă, Sorana D.
Jäntschi, Lorentz
author_sort Bolboacă, Sorana D.
collection PubMed
description The aim of the research was to investigate the relationship and/or occurrences in and between chemical composition information (tar, nicotine, carbon monoxide), market information (brand, manufacturer, price), and public health information (class, health warning) as well as clustering of a sample of cigarette data. A number of thirty cigarette brands have been analyzed. Six categorical (cigarette brand, manufacturer, health warnings, class) and four continuous (tar, nicotine, carbon monoxide concentrations and package price) variables were collected for investigation of chemical composition, market information and public health information. Multiple linear regression and two clusterization techniques have been applied. The study revealed interesting remarks. The carbon monoxide concentration proved to be linked with tar and nicotine concentration. The applied clusterization methods identified groups of cigarette brands that shown similar characteristics. The tar and carbon monoxide concentrations were the main criteria used in clusterization. An analysis of a largest sample could reveal more relevant and useful information regarding the similarities between cigarette brands.
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spelling pubmed-37316402013-08-02 Mapping Cigarettes Similarities using Cluster Analysis Methods Bolboacă, Sorana D. Jäntschi, Lorentz Int J Environ Res Public Health Articles The aim of the research was to investigate the relationship and/or occurrences in and between chemical composition information (tar, nicotine, carbon monoxide), market information (brand, manufacturer, price), and public health information (class, health warning) as well as clustering of a sample of cigarette data. A number of thirty cigarette brands have been analyzed. Six categorical (cigarette brand, manufacturer, health warnings, class) and four continuous (tar, nicotine, carbon monoxide concentrations and package price) variables were collected for investigation of chemical composition, market information and public health information. Multiple linear regression and two clusterization techniques have been applied. The study revealed interesting remarks. The carbon monoxide concentration proved to be linked with tar and nicotine concentration. The applied clusterization methods identified groups of cigarette brands that shown similar characteristics. The tar and carbon monoxide concentrations were the main criteria used in clusterization. An analysis of a largest sample could reveal more relevant and useful information regarding the similarities between cigarette brands. Molecular Diversity Preservation International (MDPI) 2007-03 2007-09-30 /pmc/articles/PMC3731640/ /pubmed/17911663 Text en © 2007 MDPI All rights reserved.
spellingShingle Articles
Bolboacă, Sorana D.
Jäntschi, Lorentz
Mapping Cigarettes Similarities using Cluster Analysis Methods
title Mapping Cigarettes Similarities using Cluster Analysis Methods
title_full Mapping Cigarettes Similarities using Cluster Analysis Methods
title_fullStr Mapping Cigarettes Similarities using Cluster Analysis Methods
title_full_unstemmed Mapping Cigarettes Similarities using Cluster Analysis Methods
title_short Mapping Cigarettes Similarities using Cluster Analysis Methods
title_sort mapping cigarettes similarities using cluster analysis methods
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3731640/
https://www.ncbi.nlm.nih.gov/pubmed/17911663
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