Surface-Based Body Shape Index and Its Relationship with All-Cause Mortality
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{"title"=>"Surface-based body shape index and its relationship with all-cause mortality", "type"=>"journal", "authors"=>[{"first_name"=>"Syed Ashiqur", "last_name"=>"Rahman", "scopus_author_id"=>"56564697600"}, {"first_name"=>"Donald", "last_name"=>"Adjeroh", "scopus_author_id"=>"6701456737"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"608080620", "sgr"=>"84957538110", "pmid"=>"26709925", "scopus"=>"2-s2.0-84957538110", "isbn"=>"1932-6203", "doi"=>"10.1371/journal.pone.0144639", "issn"=>"19326203"}, "id"=>"6182af4a-fb0c-34ce-b5c8-17e8f9751ee7", "abstract"=>"BACKGROUND: Obesity is a global public health challenge. In the US, for instance, obesity prevalence remains high at more than one-third of the adult population, while over two-thirds are obese or overweight. Obesity is associated with various health problems, such as diabetes, cardiovascular diseases (CVDs), depression, some forms of cancer, sleep apnea, osteoarthritis, among others. The body mass index (BMI) is one of the best known measures of obesity. The BMI, however, has serious limitations, for instance, its inability to capture the distribution of lean mass and adipose tissue, which is a better predictor of diabetes and CVDs, and its curved (\"U-shaped\") relationship with mortality hazard. Other anthropometric measures and their relation to obesity have been studied, each with its advantages and limitations. In this work, we introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality.\\n\\nMETHODS AND FINDINGS: We analyzed data on 11,808 subjects (ages 18-85), from the National Health and Human Nutrition Examination Survey (NHANES) 1999-2004, with 8-year mortality follow up. Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body surface area (BSA), vertical trunk circumference (VTC), height (H) and waist circumference (WC). The surface-based body shape index (SBSI) is defined as follows: [Formula: see text] SBSI has negative correlation with BMI and weight respectively, no correlation with WC, and shows a generally linear relationship with age. Results on mortality hazard prediction using both the Cox proportionality model, and Kaplan-Meier curves each show that SBSI outperforms currently popular body shape indices (e.g., BMI, WC, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), A Body Shape Index (ABSI)) in predicting all-cause mortality.\\n\\nCONCLUSIONS: We combine measures of both body shape and body size to construct a novel anthropometric measure, the surface-based body shape index (SBSI). SBSI is generally linear with age, and increases with increasing mortality, when compared with other popular anthropometric indices of body shape.", "link"=>"http://www.mendeley.com/research/surfacebased-body-shape-index-relationship-allcause-mortality", "reader_count"=>36, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Librarian"=>1, "Researcher"=>6, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>7, "Other"=>1, "Student > Bachelor"=>4, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Librarian"=>1, "Researcher"=>6, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>7, "Other"=>1, "Student > Bachelor"=>4, "Professor"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>2, "Unspecified"=>3, "Biochemistry, Genetics and Molecular Biology"=>1, "Nursing and Health Professions"=>6, "Mathematics"=>3, "Medicine and Dentistry"=>11, "Agricultural and Biological Sciences"=>4, "Sports and Recreations"=>1, "Psychology"=>3, "Chemistry"=>1, "Decision Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>11}, "Chemistry"=>{"Chemistry"=>1}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Psychology"=>{"Psychology"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>3}, "Unspecified"=>{"Unspecified"=>3}}, "reader_count_by_country"=>{"Poland"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2618577"], "description"=>"<p>Variation of different body shape indices with age (in years).</p>", "links"=>[], "tags"=>["wc", "Body Shape Index", "Body Shape", "body mass index", "nhanes", "bmi", "body surface area", "SBSI", "body size", "novel anthropometric measure", "Human Nutrition Examination Survey", "body shape indices", "bsa", "whr", "vtc", "absi", "Cox proportionality model", "cvd", "mortality hazard prediction", "Other anthropometric measures"], "article_id"=>1631504, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Syed Ashiqur Rahman", "Donald Adjeroh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144639.g002", "stats"=>{"downloads"=>1, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Variation_of_different_body_shape_indices_with_age_in_years_/1631504", "title"=>"Variation of different body shape indices with age (in years).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:55:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/2618578"], "description"=>"<p>(a) Female; (b) Male.</p>", "links"=>[], "tags"=>["wc", "Body Shape Index", "Body Shape", "body mass index", "nhanes", "bmi", "body surface area", "SBSI", "body size", "novel anthropometric measure", "Human Nutrition Examination Survey", "body shape indices", "bsa", "whr", "vtc", "absi", "Cox proportionality model", "cvd", "mortality hazard prediction", "Other anthropometric measures"], "article_id"=>1631505, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Syed Ashiqur Rahman", "Donald Adjeroh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144639.g003", "stats"=>{"downloads"=>1, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Variation_of_relative_death_rate_with_increasing_values_of_SBSI_z_score_/1631505", "title"=>"Variation of relative death rate with increasing values\nof SBSI z-score.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:55:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/2618579"], "description"=>"<p>The SBSI shows a better prediction performance than other body shape measures (with more separation between the curves, and less crossovers). 1st Q, 2nd Q, etc. denote respectively 1st quartile, 2nd quartile, etc.</p>", "links"=>[], "tags"=>["wc", "Body Shape Index", "Body Shape", "body mass index", "nhanes", "bmi", "body surface area", "SBSI", "body size", "novel anthropometric measure", "Human Nutrition Examination Survey", "body shape indices", "bsa", "whr", "vtc", "absi", "Cox proportionality model", "cvd", "mortality hazard prediction", "Other anthropometric measures"], "article_id"=>1631506, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Syed Ashiqur Rahman", "Donald Adjeroh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144639.g004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Kaplan_Meier_curves_for_four_body_shape_indices_using_all_subjects_/1631506", "title"=>"The Kaplan Meier curves for four body shape indices using all subjects.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:55:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/2618580"], "description"=>"<p>a: ABSI (male); b: ABSI (female); c: SBSI (male); d: SBSI (female). As expected, both measures indicate that female subjects have better survival rates when compared with male subjects. SBSI shows an overall better prediction performance than ABSI. 1st Q, 2nd Q, etc. denote respectively 1st quartile, 2nd quartile, etc.</p>", "links"=>[], "tags"=>["wc", "Body Shape Index", "Body Shape", "body mass index", "nhanes", "bmi", "body surface area", "SBSI", "body size", "novel anthropometric measure", "Human Nutrition Examination Survey", "body shape indices", "bsa", "whr", "vtc", "absi", "Cox proportionality model", "cvd", "mortality hazard prediction", "Other anthropometric measures"], "article_id"=>1631507, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Syed Ashiqur Rahman", "Donald Adjeroh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144639.g005", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_KM_curves_using_ABSI_and_SBSI_on_subjects_in_the_BMI_category_overweight_/1631507", "title"=>"The KM curves using ABSI and SBSI on subjects in the BMI category overweight.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:55:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/2618581"], "description"=>"<p>a: ABSI (male); b: ABSI (female); c: SBSI (male); d: SBSI (female).</p>", "links"=>[], "tags"=>["wc", "Body Shape Index", "Body Shape", "body mass index", "nhanes", "bmi", "body surface area", "SBSI", "body size", "novel anthropometric measure", "Human Nutrition Examination Survey", "body shape indices", "bsa", "whr", "vtc", "absi", "Cox proportionality model", "cvd", "mortality hazard prediction", "Other anthropometric measures"], "article_id"=>1631508, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Syed Ashiqur Rahman", "Donald Adjeroh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144639.g006", "stats"=>{"downloads"=>1, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_KM_curves_using_ABSI_and_SBSI_on_subjects_in_the_BMI_category_obese_I_/1631508", "title"=>"The KM curves using ABSI and SBSI on subjects in the BMI category obese I.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:55:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/2618583", "https://ndownloader.figshare.com/files/2618584", "https://ndownloader.figshare.com/files/2618585"], "description"=>"<div><p>Background</p><p>Obesity is a global public health challenge. In the US, for instance, obesity prevalence remains high at more than one-third of the adult population, while over two-thirds are obese or overweight. Obesity is associated with various health problems, such as diabetes, cardiovascular diseases (CVDs), depression, some forms of cancer, sleep apnea, osteoarthritis, among others. The body mass index (BMI) is one of the best known measures of obesity. The BMI, however, has serious limitations, for instance, its inability to capture the distribution of lean mass and adipose tissue, which is a better predictor of diabetes and CVDs, and its curved (“U-shaped”) relationship with mortality hazard. Other anthropometric measures and their relation to obesity have been studied, each with its advantages and limitations. In this work, we introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality.</p><p>Methods and Findings</p><p>We analyzed data on 11,808 subjects (ages 18–85), from the National Health and Human Nutrition Examination Survey (NHANES) 1999–2004, with 8-year mortality follow up. Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body surface area (BSA), vertical trunk circumference (VTC), height (H) and waist circumference (WC). The surface-based body shape index (SBSI) is defined as follows:</p><p><math><mrow><mi>S</mi><mi>B</mi><mi>S</mi><mi>I</mi><mo>=</mo><mrow><mrow><mo>(</mo><mi>H</mi><mrow><mn>7</mn><mo>/</mo><mn>4</mn></mrow><mo>)</mo></mrow><mrow><mo>(</mo><mi>W</mi><mi>C</mi><mrow><mn>5</mn><mo>/</mo><mn>6</mn></mrow><mo>)</mo></mrow></mrow><mrow><mi>B</mi><mi>S</mi><mi>A</mi><mi>V</mi><mi>T</mi><mi>C</mi></mrow></mrow></math>(1)</p>SBSI has negative correlation with BMI and weight respectively, no correlation with WC, and shows a generally linear relationship with age. Results on mortality hazard prediction using both the Cox proportionality model, and Kaplan-Meier curves each show that SBSI outperforms currently popular body shape indices (e.g., BMI, WC, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), A Body Shape Index (ABSI)) in predicting all-cause mortality.<p></p><p>Conclusions</p><p>We combine measures of both body shape and body size to construct a novel anthropometric measure, the surface-based body shape index (SBSI). SBSI is generally linear with age, and increases with increasing mortality, when compared with other popular anthropometric indices of body shape.</p></div>", "links"=>[], "tags"=>["wc", "Body Shape Index", "Body Shape", "body mass index", "nhanes", "bmi", "body surface area", "SBSI", "body size", "novel anthropometric measure", "Human Nutrition Examination Survey", "body shape indices", "bsa", "whr", "vtc", "absi", "Cox proportionality model", "cvd", "mortality hazard prediction", "Other anthropometric measures"], "article_id"=>1631510, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Syed Ashiqur Rahman", "Donald Adjeroh"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0144639.s001", "https://dx.doi.org/10.1371/journal.pone.0144639.s002", "https://dx.doi.org/10.1371/journal.pone.0144639.s003"], "stats"=>{"downloads"=>3, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Surface_Based_Body_Shape_Index_and_Its_Relationship_with_All_Cause_Mortality_/1631510", "title"=>"Surface-Based Body Shape Index and Its Relationship with All-Cause Mortality", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2016-01-05 14:55:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/2618576"], "description"=>"<p>The BSA and height, and VTC and height can predict the BMI categories (a, b). BSA and WC (and VTC and WC) show a non-linear relationship for a given BMI category (c, d).</p>", "links"=>[], "tags"=>["wc", "Body Shape Index", "Body Shape", "body mass index", "nhanes", "bmi", "body surface area", "SBSI", "body size", "novel anthropometric measure", "Human Nutrition Examination Survey", "body shape indices", "bsa", "whr", "vtc", "absi", "Cox proportionality model", "cvd", "mortality hazard prediction", "Other anthropometric measures"], "article_id"=>1631503, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Syed Ashiqur Rahman", "Donald Adjeroh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144639.g001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relationship_between_BSA_VTC_height_and_WC_for_given_BMI_categories_/1631503", "title"=>"Relationship between BSA, VTC, height and WC for given BMI categories.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:55:15"}

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{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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