Food Composition of the Diet in Relation to Changes in Waist Circumference Adjusted for Body Mass Index
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{"title"=>"Food composition of the diet in relation to changes in waist circumference adjusted for body mass index", "type"=>"journal", "authors"=>[{"first_name"=>"Dora", "last_name"=>"Romaguera", "scopus_author_id"=>"8161433300"}, {"first_name"=>"Lars", "last_name"=>"Ängquist", "scopus_author_id"=>"8840287900"}, {"first_name"=>"Huaidong", "last_name"=>"Du", "scopus_author_id"=>"23972384300"}, {"first_name"=>"Marianne Uhre", "last_name"=>"Jakobsen", "scopus_author_id"=>"7005562815"}, {"first_name"=>"Nita G.", "last_name"=>"Forouhi", "scopus_author_id"=>"6603478414"}, {"first_name"=>"Jytte", "last_name"=>"Halkjær", "scopus_author_id"=>"11240265800"}, {"first_name"=>"Edith J.M.", "last_name"=>"Feskens", "scopus_author_id"=>"7005435520"}, {"first_name"=>"Daphne L.", "last_name"=>"van der A", "scopus_author_id"=>"6507554942"}, {"first_name"=>"Giovanna", "last_name"=>"Masala", "scopus_author_id"=>"7004104734"}, {"first_name"=>"Annika", "last_name"=>"Steffen", "scopus_author_id"=>"26535191100"}, {"first_name"=>"Domenico", "last_name"=>"Palli", "scopus_author_id"=>"56448226000"}, {"first_name"=>"Nicholas J.", "last_name"=>"Wareham", "scopus_author_id"=>"7006224498"}, {"first_name"=>"Kim", "last_name"=>"Overvad", "scopus_author_id"=>"7007164627"}, {"first_name"=>"Anne", "last_name"=>"Tjønneland", "scopus_author_id"=>"7004990102"}, {"first_name"=>"Heiner", "last_name"=>"Boeing", "scopus_author_id"=>"7004900619"}, {"first_name"=>"Elio", "last_name"=>"Riboli", "scopus_author_id"=>"57191801446"}, {"first_name"=>"Thorkild I.", "last_name"=>"Sørensen", "scopus_author_id"=>"36043939900"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"80051824290", "doi"=>"10.1371/journal.pone.0023384", "pui"=>"362363565", "pmid"=>"21858094", "scopus"=>"2-s2.0-80051824290", "issn"=>"19326203", "isbn"=>"2005513946"}, "id"=>"d78a3414-e6f8-353d-bc33-cb7e55f7bff7", "abstract"=>"BACKGROUND Dietary factors such as low energy density and low glycemic index were associated with a lower gain in abdominal adiposity. A better understanding of which food groups/items contribute to these associations is necessary. OBJECTIVE To ascertain the association of food groups/items consumption on prospective annual changes in \"waist circumference for a given BMI\" (WC(BMI)), a proxy for abdominal adiposity. DESIGN We analyzed data from 48,631 men and women from 5 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Anthropometric measurements were obtained at baseline and after a median follow-up time of 5.5 years. WC(BMI) was defined as the residuals of waist circumference regressed on BMI, and annual change in WC(BMI) (ΔWC(BMI), cm/y) was defined as the difference between residuals at follow-up and baseline, divided by follow-up time. The association between food groups/items and ΔWC(BMI) was modelled using centre-specific adjusted linear regression, and random-effects meta-analyses to obtain pooled estimates. RESULTS Higher fruit and dairy products consumption was associated with a lower gain in WC(BMI) whereas the consumption of white bread, processed meat, margarine, and soft drinks was positively associated with ΔWC(BMI). When these six food groups/items were analyzed in combination using a summary score, those in the highest quartile of the score--indicating a more favourable dietary pattern--showed a ΔWC(BMI) of -0.11 (95% CI -0.09 to -0.14) cm/y compared to those in the lowest quartile. CONCLUSION A dietary pattern high in fruit and dairy and low in white bread, processed meat, margarine, and soft drinks may help to prevent abdominal fat accumulation.", "link"=>"http://www.mendeley.com/research/food-composition-diet-relation-changes-waist-circumference-adjusted-body-mass-index-2", "reader_count"=>48, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>6, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>5, "Student > Master"=>10, "Other"=>3, "Student > Bachelor"=>6, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>6, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>5, "Student > Master"=>10, "Other"=>3, "Student > Bachelor"=>6, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Biochemistry, Genetics and Molecular Biology"=>1, "Nursing and Health Professions"=>4, "Materials Science"=>1, "Agricultural and Biological Sciences"=>11, "Medicine and Dentistry"=>15, "Arts and Humanities"=>1, "Neuroscience"=>1, "Sports and Recreations"=>6, "Chemistry"=>2, "Social Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>15}, "Neuroscience"=>{"Neuroscience"=>1}, "Chemistry"=>{"Chemistry"=>2}, "Social Sciences"=>{"Social Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>6}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>11}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>4}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>5}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "Brazil"=>1, "Italy"=>1, "France"=>1, "Indonesia"=>1}, "group_count"=>2}

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  • {"files"=>["https://ndownloader.figshare.com/files/745378"], "description"=>"1<p>The association between food consumption and ΔWC<sub>BMI</sub> was modelled using centre-specific linear regression [adjusting for: total energy intake, age, baseline weight, baseline height, baseline WC<sub>BMI</sub>, smoking, alcohol intake, physical activity, education, follow-up duration, menopausal status (women only), and hormone replacement therapy use (women only)], and random-effect meta-analyses to evaluate heterogeneity (<i>I</i><sup>2</sup>) across study centres and to obtain pooled estimates of the associations.</p>2<p>Four models were constructed, all of them including dairy product consumption (per 100 kcal increments) plus either white bread (model 1), processed meat (model 2), margarine (model 3), or soft drinks (model 4), also in 100 kcal increments.</p>3<p>Four models were constructed, all of them including fruit consumption (per 100 kcal increments) plus either white bread (model 1), processed meat (model 2), margarine (model 3), or soft drinks (model 4), also in 100 kcal increments.</p>", "links"=>[], "tags"=>["circumference", "observed", "100", "kcal", "fruits", "dairy", "products", "replaced", "processed", "drinks", "conducted", "men", "women"], "article_id"=>415715, "categories"=>["Chemistry", "Biotechnology"], "users"=>["Dora Romaguera", "Lars Ängquist", "Huaidong Du", "Marianne Uhre Jakobsen", "Nita G. Forouhi", "Jytte Halkjær", "Edith J. M. Feskens", "Daphne L. van der A", "Giovanna Masala", "Annika Steffen", "Domenico Palli", "Nicholas J. Wareham", "Kim Overvad", "Anne Tjønneland", "Heiner Boeing", "Elio Riboli", "Thorkild I. Sørensen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0023384.t003", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimated_annual_change_in_waist_circumference_for_a_given_body_mass_index_WC_BMI_cm_y_8221_observed_when_100_kcal_of_fruits_or_100_kcal_of_dairy_products_replaced_100_kcal_of_white_bread_processed_meat_margarine_or_soft_drinks_analyses_conducted_in_men_/415715", "title"=>"Estimated annual change in “waist circumference for a given body mass index (ΔWC<sub>BMI</sub>, cm/y)” observed when 100 kcal of fruits or 100 kcal of dairy products replaced 100 kcal of white bread, processed meat, margarine, or soft drinks (analyses conducted in men and women combined).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-08-17 01:35:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/745311"], "description"=>"1<p>The effect of foods was studied per 100 kcal increments in intake, except for coffee and tea that were studied per 100 g increments due to their very low energy content.</p>2<p>The association between food consumption and ΔWC<sub>BMI</sub> was modelled using centre-specific linear regression [adjusting for: total energy intake, age, baseline weight, baseline height, baseline WC<sub>BMI</sub>, smoking, alcohol intake (except in the models including alcoholic beverages), physical activity, education, follow-up duration, menopausal status (women only), and hormone replacement therapy use (women only)], and random-effect meta-analyses to evaluate heterogeneity (<i>I</i><sup>2</sup>) across study centres and to obtain pooled estimates of the associations.</p><p>*indicates that there is heterogeneity across study centres (<i>P</i> for heterogeneity <0.05).</p>3<p>After excluding Italy where this food group was not assessed in their FFQ.</p>4<p>Effect modification by gender was considered relevant when the p for interaction between the exposure of interest and gender was <0.01 in ≥3 out of the 6 study centres. Only Beer consumption met this criterion.</p>", "links"=>[], "tags"=>["groups", "circumference"], "article_id"=>415666, "categories"=>["Chemistry", "Biotechnology"], "users"=>["Dora Romaguera", "Lars Ängquist", "Huaidong Du", "Marianne Uhre Jakobsen", "Nita G. Forouhi", "Jytte Halkjær", "Edith J. M. Feskens", "Daphne L. van der A", "Giovanna Masala", "Annika Steffen", "Domenico Palli", "Nicholas J. Wareham", "Kim Overvad", "Anne Tjønneland", "Heiner Boeing", "Elio Riboli", "Thorkild I. Sørensen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0023384.t002", "stats"=>{"downloads"=>3, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimated_association_between_food_groups_consumption_1_and_annual_change_in_waist_circumference_for_a_given_body_mass_index_WC_BMI_cm_y_8221_/415666", "title"=>"Estimated association between food groups consumption<sup>1</sup> and annual change in “waist circumference for a given body mass index (ΔWC<sub>BMI</sub>, cm/y)”.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-08-17 01:34:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/745252"], "description"=>"1<p>The range of exposure was expressed as the minimum and maximum mean consumption observed among the participating centres (Italy-Florence; UK-Norfolk; Netherlands-Amsterdam/Maastricht; Netherlands-Doetinchem; Germany-Potsdam; Denmark-Copenhagen/Aarhus).</p>2<p>These calculations were computed after excluding Italy where this food group was not assessed in their FFQ.</p>", "links"=>[], "tags"=>["epic-diogenes"], "article_id"=>415609, "categories"=>["Chemistry", "Biotechnology"], "users"=>["Dora Romaguera", "Lars Ängquist", "Huaidong Du", "Marianne Uhre Jakobsen", "Nita G. Forouhi", "Jytte Halkjær", "Edith J. M. Feskens", "Daphne L. van der A", "Giovanna Masala", "Annika Steffen", "Domenico Palli", "Nicholas J. Wareham", "Kim Overvad", "Anne Tjønneland", "Heiner Boeing", "Elio Riboli", "Thorkild I. Sørensen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0023384.t001", "stats"=>{"downloads"=>3, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_consumption_of_food_groups_items_g_d_by_gender_in_participants_of_the_EPIC_DiOGenes_project_n_8202_8202_48_631_/415609", "title"=>"Average consumption of food groups/items (g/d) by gender in participants of the EPIC-DiOGenes project (n = 48,631).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-08-17 01:33:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/745111"], "description"=>"<p>The association between the quartiles of the summary score (quartile 1 or Q1 is the reference category) and ΔWC<sub>BMI</sub> was modelled using centre-specific linear regression [adjusting for: total energy intake, age, baseline weight, baseline height, baseline WC<sub>BMI</sub>, smoking, alcohol intake, physical activity, education, follow-up duration, menopausal status (women only), and hormone replacement therapy use (women only)], and random-effect meta-analyses to obtain pooled estimates of the associations.</p>", "links"=>[], "tags"=>["reflecting", "dietary", "dairy", "processed", "drinks", "circumference"], "article_id"=>415450, "categories"=>["Chemistry", "Biotechnology"], "users"=>["Dora Romaguera", "Lars Ängquist", "Huaidong Du", "Marianne Uhre Jakobsen", "Nita G. Forouhi", "Jytte Halkjær", "Edith J. M. Feskens", "Daphne L. van der A", "Giovanna Masala", "Annika Steffen", "Domenico Palli", "Nicholas J. Wareham", "Kim Overvad", "Anne Tjønneland", "Heiner Boeing", "Elio Riboli", "Thorkild I. Sørensen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0023384.g001", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimated_global_association_between_a_summary_score_reflecting_a_dietary_pattern_with_a_high_content_of_fruit_and_dairy_products_and_low_content_of_white_bread_processed_meat_margarine_and_soft_drinks_and_annual_change_in_waist_circumference_for_a_given/415450", "title"=>"Estimated global association between a summary score reflecting a dietary pattern with a high content of fruit and dairy products, and low content of white bread, processed meat, margarine, and soft drinks and annual change in “waist circumference for a given body mass index (ΔWC<sub>BMI</sub>, cm/y)”.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-08-17 01:30:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/375606", "https://ndownloader.figshare.com/files/375664"], "description"=>"<div><h3>Background</h3><p>Dietary factors such as low energy density and low glycemic index were associated with a lower gain in abdominal adiposity. A better understanding of which food groups/items contribute to these associations is necessary.</p> <h3>Objective</h3><p>To ascertain the association of food groups/items consumption on prospective annual changes in “waist circumference for a given BMI” (WC<sub>BMI</sub>), a proxy for abdominal adiposity.</p> <h3>Design</h3><p>We analyzed data from 48,631 men and women from 5 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Anthropometric measurements were obtained at baseline and after a median follow-up time of 5.5 years. WC<sub>BMI</sub> was defined as the residuals of waist circumference regressed on BMI, and annual change in WC<sub>BMI</sub> (ΔWC<sub>BMI</sub>, cm/y) was defined as the difference between residuals at follow-up and baseline, divided by follow-up time. The association between food groups/items and ΔWC<sub>BMI</sub> was modelled using centre-specific adjusted linear regression, and random-effects meta-analyses to obtain pooled estimates.</p> <h3>Results</h3><p>Higher fruit and dairy products consumption was associated with a lower gain in WC<sub>BMI</sub> whereas the consumption of white bread, processed meat, margarine, and soft drinks was positively associated with ΔWC<sub>BMI</sub>. When these six food groups/items were analyzed in combination using a summary score, those in the highest quartile of the score – indicating a more favourable dietary pattern –showed a ΔWC<sub>BMI</sub> of −0.11 (95% CI −0.09 to −0.14) cm/y compared to those in the lowest quartile.</p> <h3>Conclusion</h3><p>A dietary pattern high in fruit and dairy and low in white bread, processed meat, margarine, and soft drinks may help to prevent abdominal fat accumulation.</p> </div>", "links"=>[], "tags"=>["changes", "circumference", "adjusted"], "article_id"=>134191, "categories"=>["Chemistry", "Biotechnology"], "users"=>["Dora Romaguera", "Lars Ängquist", "Huaidong Du", "Marianne Uhre Jakobsen", "Nita G. Forouhi", "Jytte Halkjær", "Edith J. M. Feskens", "Daphne L. van der A", "Giovanna Masala", "Annika Steffen", "Domenico Palli", "Nicholas J. Wareham", "Kim Overvad", "Anne Tjønneland", "Heiner Boeing", "Elio Riboli", "Thorkild I. Sørensen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023384.s001", "https://dx.doi.org/10.1371/journal.pone.0023384.s002"], "stats"=>{"downloads"=>4, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Food_Composition_of_the_Diet_in_Relation_to_Changes_in_Waist_Circumference_Adjusted_for_Body_Mass_Index/134191", "title"=>"Food Composition of the Diet in Relation to Changes in Waist Circumference Adjusted for Body Mass Index", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-08-17 01:09:51"}

PMC Usage Stats | Further Information

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