Associations of Supermarket Characteristics with Weight Status and Body Fat: A Multilevel Analysis of Individuals within Supermarkets (RECORD Study)
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{"title"=>"Associations of supermarket characteristics with weight status and body fat: A multilevel analysis of individuals within supermarkets (record study)", "type"=>"journal", "authors"=>[{"first_name"=>"Basile", "last_name"=>"Chaix", "scopus_author_id"=>"8654719200"}, {"first_name"=>"Kathy", "last_name"=>"Bean", "scopus_author_id"=>"7006591047"}, {"first_name"=>"Mark", "last_name"=>"Daniel", "scopus_author_id"=>"7202420971"}, {"first_name"=>"Shannon N.", "last_name"=>"Zenk", "scopus_author_id"=>"9733165200"}, {"first_name"=>"Yan", "last_name"=>"Kestens", "scopus_author_id"=>"55906994500"}, {"first_name"=>"Hélène", "last_name"=>"Charreire", "scopus_author_id"=>"16204957000"}, {"first_name"=>"Cinira", "last_name"=>"Leal", "scopus_author_id"=>"35272597100"}, {"first_name"=>"Frédérique", "last_name"=>"Thomas", "scopus_author_id"=>"7401928912"}, {"first_name"=>"Noëlla", "last_name"=>"Karusisi", "scopus_author_id"=>"55173928700"}, {"first_name"=>"Christiane", "last_name"=>"Weber", "scopus_author_id"=>"55172874400"}, {"first_name"=>"Jean Michel", "last_name"=>"Oppert", "scopus_author_id"=>"7003273891"}, {"first_name"=>"Chantal", "last_name"=>"Simon", "scopus_author_id"=>"7401973746"}, {"first_name"=>"Juan", "last_name"=>"Merlo", "scopus_author_id"=>"55173309900"}, {"first_name"=>"Bruno", "last_name"=>"Pannier", "scopus_author_id"=>"7006409178"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84859308710", "pmid"=>"22496738", "doi"=>"10.1371/journal.pone.0032908", "pui"=>"364568840", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "sgr"=>"84859308710"}, "id"=>"16e073e4-58ec-3769-95be-c8cc0c5e5016", "abstract"=>"PURPOSE: Previous research on the influence of the food environment on weight status has often used impersonal measures of the food environment defined for residential neighborhoods, which ignore whether people actually use the food outlets near their residence. To assess whether supermarkets are relevant contexts for interventions, the present study explored between-residential neighborhood and between-supermarket variations in body mass index (BMI) and waist circumference (WC), and investigated associations between brands and characteristics of supermarkets and BMI or WC, after adjustment for individual and residential neighborhood characteristics.\\n\\nMETHODS: Participants in the RECORD Cohort Study (Paris Region, France, 2007-2008) were surveyed on the supermarket (brand and exact location) where they conducted their food shopping. Overall, 7 131 participants shopped in 1 097 different supermarkets. Cross-classified multilevel linear models were estimated for BMI and WC.\\n\\nRESULTS: Just 11.4% of participants shopped for food primarily within their residential neighborhood. After accounting for participants' residential neighborhood, people shopping in the same supermarket had a more comparable BMI and WC than participants shopping in different supermarkets. After adjustment for individual and residential neighborhood characteristics, participants shopping in specific supermarket brands, in hard discount supermarkets (especially if they had a low education), and in supermarkets whose catchment area comprised low educated residents had a higher BMI/WC.\\n\\nCONCLUSION: A public health strategy to reduce excess weight may be to intervene on specific supermarkets to change food purchasing behavior, as supermarkets are where dietary preferences are materialized into definite purchased foods.", "link"=>"http://www.mendeley.com/research/associations-supermarket-characteristics-weight-status-body-fat-multilevel-analysis-individuals-with", "reader_count"=>76, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>2, "Researcher"=>14, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>3, "Student > Master"=>13, "Other"=>5, "Student > Bachelor"=>5, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>2, "Researcher"=>14, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>3, "Student > Master"=>13, "Other"=>5, "Student > Bachelor"=>5, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>12, "Agricultural and Biological Sciences"=>10, "Economics, Econometrics and Finance"=>1, "Engineering"=>1, "Environmental Science"=>2, "Nursing and Health Professions"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>26, "Neuroscience"=>1, "Sports and Recreations"=>1, "Physics and Astronomy"=>1, "Psychology"=>6, "Social Sciences"=>13}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>26}, "Social Sciences"=>{"Social Sciences"=>13}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>6}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>12}, "Environmental Science"=>{"Environmental Science"=>2}, "Engineering"=>{"Engineering"=>1}, "Neuroscience"=>{"Neuroscience"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>10}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "United States"=>1, "United Kingdom"=>3, "France"=>3, "Australia"=>1}, "group_count"=>10}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/658689"], "description"=>"<p>Abbreviations: BMI, body mass index; CI, confidence interval; WC, waist circumference.</p>a<p>Mean size of the supermarkets of each specific brand weighted by the number of participants using each supermarket.</p>b<p>Street-network distance from home to the participants' supermarkets.</p>c<p>Associations were estimated from cross-classified multilevel linear models adjusted for individual sociodemographic characteristics, neighborhood education, and distance to the supermarket. They were not adjusted for supermarket neighborhood education, as supermarket neighborhood SES was hypothesized to mediate the possible influence of brands.</p>", "links"=>[], "tags"=>["brands", "adjusted", "associations", "bmi", "wc", "ranked", "alphabetical", "cohort", "paris"], "article_id"=>329150, "categories"=>["Medicine", "Biotechnology"], "users"=>["Basile Chaix", "Kathy Bean", "Mark Daniel", "Shannon N. Zenk", "Yan Kestens", "Hélène Charreire", "Cinira Leal", "Frédérique Thomas", "Noëlla Karusisi", "Christiane Weber", "Jean-Michel Oppert", "Chantal Simon", "Juan Merlo", "Bruno Pannier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032908.t003", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characteristics_of_the_main_supermarket_brands_and_adjusted_associations_between_supermarket_brands_and_BMI_or_WC_brands_are_ranked_by_supermarket_type_and_alphabetical_order_RECORD_Cohort_Study_Paris_Metropolitan_Area_2007_8211_2008_/329150", "title"=>"Characteristics of the main supermarket brands and adjusted associations between supermarket brands and BMI or WC (brands are ranked by supermarket type and alphabetical order), RECORD Cohort Study, Paris Metropolitan Area, 2007–2008.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-04 02:32:30"}
  • {"files"=>["https://ndownloader.figshare.com/files/658485"], "description"=>"<p>Abbreviations: BMI, body mass index; CI, confidence interval; WC, waist circumference.</p>a<p>The following variables were simultaneously introduced into the models: individual sociodemographic characteristics, residential neighborhood education, supermarket type, distance to the supermarket, and supermarket neighborhood education.</p>b<p>Based on the AIC, supermarket neighborhood education was measured in brand-specific radius areas in the model for BMI and in 5 000 m radius areas in the model for WC.</p>", "links"=>[], "tags"=>["bmi", "cohort", "paris"], "article_id"=>328954, "categories"=>["Medicine", "Biotechnology"], "users"=>["Basile Chaix", "Kathy Bean", "Mark Daniel", "Shannon N. Zenk", "Yan Kestens", "Hélène Charreire", "Cinira Leal", "Frédérique Thomas", "Noëlla Karusisi", "Christiane Weber", "Jean-Michel Oppert", "Chantal Simon", "Juan Merlo", "Bruno Pannier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032908.t004", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Associations_a_between_residential_neighborhood_education_supermarket_type_distance_to_the_supermarket_and_supermarket_neighborhood_education_and_BMI_or_WC_RECORD_Cohort_Study_Paris_Metropolitan_Area_2007_2008_/328954", "title"=>"Associations<sup>a</sup> between residential neighborhood education, supermarket type, distance to the supermarket, and supermarket neighborhood education and BMI or WC, RECORD Cohort Study, Paris Metropolitan Area, 2007–2008.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-04 02:29:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/658525"], "description"=>"<p>Abbreviations: BMI, body mass index; CI, confidence interval; WC, waist circumference.</p>a<p>The models were adjusted for individual sociodemographic characteristics. Due to the low sample sizes after matching, the models reported here (before and after matching) are not adjusted for neighborhood education or other supermarket variables.</p>", "links"=>[], "tags"=>["bmi", "wc", "matching", "propensity", "cohort", "paris"], "article_id"=>328999, "categories"=>["Medicine", "Biotechnology"], "users"=>["Basile Chaix", "Kathy Bean", "Mark Daniel", "Shannon N. Zenk", "Yan Kestens", "Hélène Charreire", "Cinira Leal", "Frédérique Thomas", "Noëlla Karusisi", "Christiane Weber", "Jean-Michel Oppert", "Chantal Simon", "Juan Merlo", "Bruno Pannier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032908.t005", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Associations_a_between_supermarket_type_and_BMI_or_WC_before_and_after_matching_on_the_propensity_of_exposure_RECORD_Cohort_Study_Paris_Metropolitan_Area_2007_2008_/328999", "title"=>"Associations<sup>a</sup> between supermarket type and BMI or WC before and after matching on the propensity of exposure, RECORD Cohort Study, Paris Metropolitan Area, 2007–2008.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-04 02:29:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/658383"], "description"=>"<p>Directed acyclic graph describing the hypothesized relationships.</p>", "links"=>[], "tags"=>["acyclic", "graph", "describing", "hypothesized"], "article_id"=>328847, "categories"=>["Medicine", "Biotechnology"], "users"=>["Basile Chaix", "Kathy Bean", "Mark Daniel", "Shannon N. Zenk", "Yan Kestens", "Hélène Charreire", "Cinira Leal", "Frédérique Thomas", "Noëlla Karusisi", "Christiane Weber", "Jean-Michel Oppert", "Chantal Simon", "Juan Merlo", "Bruno Pannier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032908.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Directed_acyclic_graph_describing_the_hypothesized_relationships_/328847", "title"=>"Directed acyclic graph describing the hypothesized relationships.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-04 02:27:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/658575"], "description"=>"a<p>The analytic scales refer to the levels accounted for in the multilevel models, while the measurement scales refer to the levels of definition of the different variables. Expressions in italic indicate (i) that exposure to neighborhood socioeconomic conditions was assessed at the individual level within circular areas centered on residences; (ii) that the supermarket-level variable on the quality of fruits and vegetables was based on the aggregation of individual perceptions; and (iii) that the distance to the supermarket was assessed at the individual level.</p>", "links"=>[], "tags"=>["scales", "considered", "analyses"], "article_id"=>329040, "categories"=>["Medicine", "Biotechnology"], "users"=>["Basile Chaix", "Kathy Bean", "Mark Daniel", "Shannon N. Zenk", "Yan Kestens", "Hélène Charreire", "Cinira Leal", "Frédérique Thomas", "Noëlla Karusisi", "Christiane Weber", "Jean-Michel Oppert", "Chantal Simon", "Juan Merlo", "Bruno Pannier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032908.t001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_the_scales_considered_in_the_analyses_hierarchical_modeling_and_in_the_measurement_of_the_variables_a_/329040", "title"=>"Summary of the scales considered in the analyses (hierarchical modeling) and in the measurement of the variables<sup>a</sup>.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-04 02:30:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/337726", "https://ndownloader.figshare.com/files/337807", "https://ndownloader.figshare.com/files/337890", "https://ndownloader.figshare.com/files/338002", "https://ndownloader.figshare.com/files/338092", "https://ndownloader.figshare.com/files/338161", "https://ndownloader.figshare.com/files/338285"], "description"=>"<div><h3>Purpose</h3><p>Previous research on the influence of the food environment on weight status has often used impersonal measures of the food environment defined for residential neighborhoods, which ignore whether people actually use the food outlets near their residence. To assess whether supermarkets are relevant contexts for interventions, the present study explored between-residential neighborhood and between-supermarket variations in body mass index (BMI) and waist circumference (WC), and investigated associations between brands and characteristics of supermarkets and BMI or WC, after adjustment for individual and residential neighborhood characteristics.</p> <h3>Methods</h3><p>Participants in the RECORD Cohort Study (Paris Region, France, 2007–2008) were surveyed on the supermarket (brand and exact location) where they conducted their food shopping. Overall, 7 131 participants shopped in 1 097 different supermarkets. Cross-classified multilevel linear models were estimated for BMI and WC.</p> <h3>Results</h3><p>Just 11.4% of participants shopped for food primarily within their residential neighborhood. After accounting for participants' residential neighborhood, people shopping in the same supermarket had a more comparable BMI and WC than participants shopping in different supermarkets. After adjustment for individual and residential neighborhood characteristics, participants shopping in specific supermarket brands, in hard discount supermarkets (especially if they had a low education), and in supermarkets whose catchment area comprised low educated residents had a higher BMI/WC.</p> <h3>Conclusion</h3><p>A public health strategy to reduce excess weight may be to intervene on specific supermarkets to change food purchasing behavior, as supermarkets are where dietary preferences are materialized into definite purchased foods.</p> </div>", "links"=>[], "tags"=>["associations", "characteristics", "multilevel", "individuals", "supermarkets"], "article_id"=>126745, "categories"=>["Medicine", "Biotechnology"], "users"=>["Basile Chaix", "Kathy Bean", "Mark Daniel", "Shannon N. Zenk", "Yan Kestens", "Hélène Charreire", "Cinira Leal", "Frédérique Thomas", "Noëlla Karusisi", "Christiane Weber", "Jean-Michel Oppert", "Chantal Simon", "Juan Merlo", "Bruno Pannier"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0032908.s001", "https://dx.doi.org/10.1371/journal.pone.0032908.s002", "https://dx.doi.org/10.1371/journal.pone.0032908.s003", "https://dx.doi.org/10.1371/journal.pone.0032908.s004", "https://dx.doi.org/10.1371/journal.pone.0032908.s005", "https://dx.doi.org/10.1371/journal.pone.0032908.s006", "https://dx.doi.org/10.1371/journal.pone.0032908.s007"], "stats"=>{"downloads"=>27, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Associations_of_Supermarket_Characteristics_with_Weight_Status_and_Body_Fat_A_Multilevel_Analysis_of_Individuals_within_Supermarkets_RECORD_Study_/126745", "title"=>"Associations of Supermarket Characteristics with Weight Status and Body Fat: A Multilevel Analysis of Individuals within Supermarkets (RECORD Study)", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-04-04 01:52:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/658626"], "description"=>"a<p>Variables were computed on different scales, with a circular radius from 100 to 10 000 m. Socioeconomic status of supermarket catchment areas was also determined within circular areas with a varying radius corresponding to the 75<sup>th</sup> percentile of the straight-line distance from home to the participants' primary supermarkets of each particular brand (brand-specific scales).</p>b<p>These variables were missing for the supermarkets utilized by 6.5% of the participants.</p>", "links"=>[], "tags"=>["neighborhood-level", "supermarket-level", "variables", "cohort", "paris"], "article_id"=>329098, "categories"=>["Medicine", "Biotechnology"], "users"=>["Basile Chaix", "Kathy Bean", "Mark Daniel", "Shannon N. Zenk", "Yan Kestens", "Hélène Charreire", "Cinira Leal", "Frédérique Thomas", "Noëlla Karusisi", "Christiane Weber", "Jean-Michel Oppert", "Chantal Simon", "Juan Merlo", "Bruno Pannier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032908.t002", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Description_of_the_individual_level_residential_neighborhood_level_and_supermarket_level_variables_analyzed_RECORD_Cohort_Study_Paris_Metropolitan_Area_2007_8211_2008_/329098", "title"=>"Description of the individual-level, residential neighborhood-level and supermarket-level variables analyzed, RECORD Cohort Study, Paris Metropolitan Area, 2007–2008.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-04 02:31:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/658291"], "description"=>"<p>The interactions were estimated from cross-classified multilevel linear models for body mass index (BMI) (part A) and waist circumference (WC) (part B) adjusted for individual sociodemographic characteristics, residential neighborhood education, supermarket type, distance to the supermarket, and supermarket neighborhood education (interactions assessed with a variable combining categories of the two variables). RECORD Cohort Study, Paris Metropolitan Area, 2007–2008.</p>", "links"=>[], "tags"=>["discounts", "anthropometric"], "article_id"=>328761, "categories"=>["Medicine", "Biotechnology"], "users"=>["Basile Chaix", "Kathy Bean", "Mark Daniel", "Shannon N. Zenk", "Yan Kestens", "Hélène Charreire", "Cinira Leal", "Frédérique Thomas", "Noëlla Karusisi", "Christiane Weber", "Jean-Michel Oppert", "Chantal Simon", "Juan Merlo", "Bruno Pannier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0032908.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Interactions_between_effects_of_individual_education_and_shopping_in_hard_discounts_on_the_anthropometric_variables_/328761", "title"=>"Interactions between effects of individual education and shopping in hard discounts on the anthropometric variables.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-04 02:26:01"}

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Relative Metric

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