Focused Principal Component Analysis: a graphical method for exploring dietary patterns
Main Author: | |
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Publication Date: | 2010 |
Other Authors: | , , , |
Format: | Article |
Language: | eng |
Source: | Cadernos de Saúde Pública |
Download full: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2010001100016 |
Summary: | The aim of the present study was to introduce Focused Principal Component Analysis (FPCA) as a novel exploratory method for providing insight into dietary patterns that emerge based on a given characteristic of the sample. To demonstrate the use of FPCA, we used a database of 1,968 adults. Food intake was obtained using a food frequency questionnaire covering 26 food items. The focus variables used for analysis were age, income, and schooling. All analyses were carried out using R software. The graphs generated show evidence of socioeconomic inequities in dietary patterns. Intake of whole-wheat foods, fruit, and vegetables was positively correlated with income and schooling, whereas for refined cereals, animal fats (lard), and white bread this correlation was negative. Age was inversely associated with intake of fast-food and processed foods and directly associated with a pattern that included fruit, green salads, and other vegetables. In an easy and direct fashion, FPCA allowed us to visualize dietary patterns based on a given focus variable. |
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Focused Principal Component Analysis: a graphical method for exploring dietary patternsFood ConsumptionPrincipal Component AnalysisNutritional EpidemiologyThe aim of the present study was to introduce Focused Principal Component Analysis (FPCA) as a novel exploratory method for providing insight into dietary patterns that emerge based on a given characteristic of the sample. To demonstrate the use of FPCA, we used a database of 1,968 adults. Food intake was obtained using a food frequency questionnaire covering 26 food items. The focus variables used for analysis were age, income, and schooling. All analyses were carried out using R software. The graphs generated show evidence of socioeconomic inequities in dietary patterns. Intake of whole-wheat foods, fruit, and vegetables was positively correlated with income and schooling, whereas for refined cereals, animal fats (lard), and white bread this correlation was negative. Age was inversely associated with intake of fast-food and processed foods and directly associated with a pattern that included fruit, green salads, and other vegetables. In an easy and direct fashion, FPCA allowed us to visualize dietary patterns based on a given focus variable.Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz2010-11-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2010001100016Cadernos de Saúde Pública v.26 n.11 2010reponame:Cadernos de Saúde Públicainstname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZ10.1590/S0102-311X2010001100016info:eu-repo/semantics/openAccessCanuto,RaquelCamey,SuziGigante,Denise P.Menezes,Ana M. B.Olinto,Maria Teresa Anselmoeng2010-12-15T00:00:00Zoai:scielo:S0102-311X2010001100016Revistahttp://cadernos.ensp.fiocruz.br/csp/https://old.scielo.br/oai/scielo-oai.phpcadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br1678-44640102-311Xopendoar:2010-12-15T00:00Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ)false |
dc.title.none.fl_str_mv |
Focused Principal Component Analysis: a graphical method for exploring dietary patterns |
title |
Focused Principal Component Analysis: a graphical method for exploring dietary patterns |
spellingShingle |
Focused Principal Component Analysis: a graphical method for exploring dietary patterns Canuto,Raquel Food Consumption Principal Component Analysis Nutritional Epidemiology |
title_short |
Focused Principal Component Analysis: a graphical method for exploring dietary patterns |
title_full |
Focused Principal Component Analysis: a graphical method for exploring dietary patterns |
title_fullStr |
Focused Principal Component Analysis: a graphical method for exploring dietary patterns |
title_full_unstemmed |
Focused Principal Component Analysis: a graphical method for exploring dietary patterns |
title_sort |
Focused Principal Component Analysis: a graphical method for exploring dietary patterns |
author |
Canuto,Raquel |
author_facet |
Canuto,Raquel Camey,Suzi Gigante,Denise P. Menezes,Ana M. B. Olinto,Maria Teresa Anselmo |
author_role |
author |
author2 |
Camey,Suzi Gigante,Denise P. Menezes,Ana M. B. Olinto,Maria Teresa Anselmo |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Canuto,Raquel Camey,Suzi Gigante,Denise P. Menezes,Ana M. B. Olinto,Maria Teresa Anselmo |
dc.subject.por.fl_str_mv |
Food Consumption Principal Component Analysis Nutritional Epidemiology |
topic |
Food Consumption Principal Component Analysis Nutritional Epidemiology |
description |
The aim of the present study was to introduce Focused Principal Component Analysis (FPCA) as a novel exploratory method for providing insight into dietary patterns that emerge based on a given characteristic of the sample. To demonstrate the use of FPCA, we used a database of 1,968 adults. Food intake was obtained using a food frequency questionnaire covering 26 food items. The focus variables used for analysis were age, income, and schooling. All analyses were carried out using R software. The graphs generated show evidence of socioeconomic inequities in dietary patterns. Intake of whole-wheat foods, fruit, and vegetables was positively correlated with income and schooling, whereas for refined cereals, animal fats (lard), and white bread this correlation was negative. Age was inversely associated with intake of fast-food and processed foods and directly associated with a pattern that included fruit, green salads, and other vegetables. In an easy and direct fashion, FPCA allowed us to visualize dietary patterns based on a given focus variable. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-11-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2010001100016 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2010001100016 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0102-311X2010001100016 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz |
publisher.none.fl_str_mv |
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz |
dc.source.none.fl_str_mv |
Cadernos de Saúde Pública v.26 n.11 2010 reponame:Cadernos de Saúde Pública instname:Fundação Oswaldo Cruz (FIOCRUZ) instacron:FIOCRUZ |
instname_str |
Fundação Oswaldo Cruz (FIOCRUZ) |
instacron_str |
FIOCRUZ |
institution |
FIOCRUZ |
reponame_str |
Cadernos de Saúde Pública |
collection |
Cadernos de Saúde Pública |
repository.name.fl_str_mv |
Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ) |
repository.mail.fl_str_mv |
cadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br |
_version_ |
1754115730748473344 |