Waist Circumference and Body Mass Index as Predictors of Health Care Costs
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{"title"=>"Waist circumference and body mass index as predictors of health care costs", "type"=>"journal", "authors"=>[{"first_name"=>"Betina", "last_name"=>"Højgaard", "scopus_author_id"=>"25421650500"}, {"first_name"=>"Dorte", "last_name"=>"Gyrd-Hansen", "scopus_author_id"=>"7004595532"}, {"first_name"=>"Kim Rose", "last_name"=>"Olsen", "scopus_author_id"=>"9239226300"}, {"first_name"=>"Jes", "last_name"=>"Søgaard", "scopus_author_id"=>"6603836876"}, {"first_name"=>"Thorkild I.A.", "last_name"=>"Sørensen", "scopus_author_id"=>"36043939900"}], "year"=>2008, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"50349096197", "doi"=>"10.1371/journal.pone.0002619", "pui"=>"352240539", "pmid"=>"18612430", "scopus"=>"2-s2.0-50349096197", "issn"=>"19326203"}, "id"=>"8806e17e-397a-3ed1-b608-961e5c666ef8", "abstract"=>"BACKGROUND In the present study we analyze the relationship between body mass index (BMI) and waist circumference (WC) and future health care costs. On the basis of the relation between these anthropometric measures and mortality, we hypothesized that for all levels of BMI increased WC implies added future health care costs (Hypothesis 1) and for given levels of WC increased BMI entails reduced future health care costs (Hypothesis 2). We furthermore assessed whether a combination of the two measures predicts health care costs better than either individual measure. RESEARCH METHODOLOGY/PRINCIPAL FINDINGS Data were obtained from the Danish prospective cohort study Diet, Cancer and Health. The population includes 15,334 men and 16,506 women 50 to 64 years old recruited in 1996 to 1997. The relationship between future health care costs and BMI and WC in combination was analyzed by use of categorized and continuous analyses. The analysis confirms Hypothesis 1, reflecting that an increased level of abdominal fat for a given BMI gives higher health care costs. Hypothesis 2, that BMI had a protective effect for a given WC, was only confirmed in the continuous analysis and for a subgroup of women (BMI<30 kg/m(2) and WC <88 cm). The relative magnitude of the estimates supports that the regressions including WC as an explanatory factor provide the best fit to the data. CONCLUSION The study showed that WC for given levels of BMI predicts increased health costs, whereas BMI for given WC did not predict health costs except for a lower cost in non-obese women with normal WC. Combining WC and BMI does not give a better prediction of costs than WC alone.", "link"=>"http://www.mendeley.com/research/waist-circumference-body-mass-index-predictors-health-care-costs-1", "reader_count"=>25, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>4, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>2, "Student > Postgraduate"=>1, "Student > Master"=>6, "Student > Bachelor"=>5, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>4, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>2, "Student > Postgraduate"=>1, "Student > Master"=>6, "Student > Bachelor"=>5, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Environmental Science"=>1, "Nursing and Health Professions"=>2, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>14, "Agricultural and Biological Sciences"=>1, "Sports and Recreations"=>3, "Social Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>14}, "Social Sciences"=>{"Social Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"Denmark"=>1, "Italy"=>1, "Chile"=>1}, "group_count"=>1}

Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/927171"], "description"=>"<p><sup>*</sup>, <sup>**</sup> and <sup>***</sup> indicate statistical significance at the 5%, 1% and 0.1% level.</p>†<p>Model 5 run the model specification applied in model 3 on the subgroup of individuals with BMI<30 kg/m<sup>2</sup> and WC <88 cm for women and 102 cm for men</p>", "links"=>[], "tags"=>["wc", "confounders", "included", "estimates"], "article_id"=>597619, "categories"=>["Medicine", "Biotechnology"], "users"=>["Betina Højgaard", "Dorte Gyrd-Hansen", "Kim Rose Olsen", "Jes Søgaard", "Thorkild I. A. Sørensen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0002619.t005", "stats"=>{"downloads"=>6, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_association_between_health_care_cost_BMI_WC_and_BMI_215_WC_Note_that_constant_term_and_potential_confounders_are_included_in_the_analysis_but_the_estimates_are_not_reported_/597619", "title"=>"The association between health care cost, BMI, WC and BMI×WC. Note that constant term and potential confounders are included in the analysis, but the estimates are not reported", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 10:03:20"}
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  • {"files"=>["https://ndownloader.figshare.com/files/927032"], "description"=>"<p>Baseline characteristics of the 31,840 eligible participants with complete data (16,506 women and 15,334 men)</p>", "links"=>[], "tags"=>["women"], "article_id"=>597480, "categories"=>["Medicine", "Biotechnology"], "users"=>["Betina Højgaard", "Dorte Gyrd-Hansen", "Kim Rose Olsen", "Jes Søgaard", "Thorkild I. A. Sørensen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0002619.t002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Baseline_characteristics_of_the_31_840_eligible_participants_with_complete_data_16_506_women_and_15_334_men_/597480", "title"=>"Baseline characteristics of the 31,840 eligible participants with complete data (16,506 women and 15,334 men)", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 10:02:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/927067"], "description"=>"*<p>Definition of the WC categories, see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002619#pone-0002619-t001\" target=\"_blank\">table 1</a>.</p>", "links"=>[], "tags"=>["subjects", "circumference", "bmi"], "article_id"=>597518, "categories"=>["Medicine", "Biotechnology"], "users"=>["Betina Højgaard", "Dorte Gyrd-Hansen", "Kim Rose Olsen", "Jes Søgaard", "Thorkild I. A. Sørensen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0002619.t003", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_the_subjects_according_to_the_3_waist_circumference_WC_and_3_BMI_categories_in_combination_/597518", "title"=>"Distribution of the subjects according to the 3 waist circumference (WC) and 3 BMI categories, in combination.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 10:02:46"}

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Relative Metric

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