Optimal Central Obesity Measurement Site for Assessing Cardiometabolic and Type 2 Diabetes Risk in Middle-Aged Adults
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{"title"=>"Optimal central obesity measurement site for assessing cardiometabolic and type 2 diabetes risk in middle-aged adults", "type"=>"journal", "authors"=>[{"first_name"=>"Seán R.", "last_name"=>"Millar", "scopus_author_id"=>"56080009600"}, {"first_name"=>"Ivan J.", "last_name"=>"Perry", "scopus_author_id"=>"35353505400"}, {"first_name"=>"Jan", "last_name"=>"Van Den Broeck", "scopus_author_id"=>"7004618191"}, {"first_name"=>"Catherine M.", "last_name"=>"Phillips", "scopus_author_id"=>"7403135902"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"604911792", "doi"=>"10.1371/journal.pone.0129088", "sgr"=>"84935028010", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"26042771", "scopus"=>"2-s2.0-84935028010"}, "id"=>"4795feed-d5d7-3038-b2c0-4811ab30ac77", "abstract"=>"OBJECTIVES Despite recommendations that central obesity assessment should be employed as a marker of cardiometabolic health, no consensus exists regarding measurement protocol. This study examined a range of anthropometric variables and their relationships with cardiometabolic features and type 2 diabetes in order to ascertain whether measurement site influences discriminatory accuracy. In particular, we compared waist circumference (WC) measured at two sites: (1) immediately below the lowest rib (WC rib) and (2) between the lowest rib and iliac crest (WC midway), which has been recommended by the World Health Organisation and International Diabetes Federation. MATERIALS AND METHODS This was a cross-sectional study involving a random sample of 2,002 men and women aged 46-73 years. Metabolic profiles and WC, hip circumference, pelvic width and body mass index (BMI) were determined. Correlation, logistic regression and area under the receiver operating characteristic curve analyses were used to evaluate obesity measurement relationships with metabolic risk phenotypes and type 2 diabetes. RESULTS WC rib measures displayed the strongest associations with non-optimal lipid and lipoprotein levels, high blood pressure, insulin resistance, impaired fasting glucose, a clustering of metabolic risk features and type 2 diabetes, in both genders. Rib-derived indices improved discrimination of type 2 diabetes by 3-7% compared to BMI and 2-6% compared to WC midway (in men) and 5-7% compared to BMI and 4-6% compared to WC midway (in women). A prediction model including BMI and central obesity displayed a significantly higher area under the curve for WC rib (0.78, P=0.003), Rib/height ratio (0.80, P<0.001), Rib/pelvis ratio (0.79, P<0.001), but not for WC midway (0.75, P=0.127), when compared to one with BMI alone (0.74). CONCLUSIONS WC rib is easier to assess and our data suggest that it is a better method for determining obesity-related cardiometabolic risk than WC midway. The clinical utility of rib-derived indices, or alternative WC measurements, deserves further investigation.", "link"=>"http://www.mendeley.com/research/optimal-central-obesity-measurement-site-assessing-cardiometabolic-type-2-diabetes-risk-middleaged-a", "reader_count"=>25, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Researcher"=>2, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>5, "Student > Master"=>4, "Student > Bachelor"=>3, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Researcher"=>2, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>5, "Student > Master"=>4, "Student > Bachelor"=>3, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Biochemistry, Genetics and Molecular Biology"=>2, "Nursing and Health Professions"=>3, "Medicine and Dentistry"=>13, "Agricultural and Biological Sciences"=>1, "Arts and Humanities"=>1, "Social Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>13}, "Social Sciences"=>{"Social Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Unspecified"=>{"Unspecified"=>4}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "Taiwan"=>1, "Malaysia"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2095474"], "description"=>"<p>Bars represent AUC values. Statistical differences in the AUC values are shown in superscript Arabic numbers as: <sup>1</sup>P<0.05 compared to WC midway; <sup>2</sup>P<0.05 compared to BMI.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436480, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g004", "stats"=>{"downloads"=>0, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Adjusted_area_under_the_receiver_operating_characteristic_curve_values_for_selected_obesity_measures_to_discriminate_subjects_with_type_2_diabetes_/1436480", "title"=>"Adjusted area under the receiver operating characteristic curve values for selected obesity measures to discriminate subjects with type 2 diabetes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095493"], "description"=>"<div><p>Objectives</p><p>Despite recommendations that central obesity assessment should be employed as a marker of cardiometabolic health, no consensus exists regarding measurement protocol. This study examined a range of anthropometric variables and their relationships with cardiometabolic features and type 2 diabetes in order to ascertain whether measurement site influences discriminatory accuracy. In particular, we compared waist circumference (WC) measured at two sites: (1) immediately below the lowest rib (WC rib) and (2) between the lowest rib and iliac crest (WC midway), which has been recommended by the World Health Organisation and International Diabetes Federation.</p><p>Materials and Methods</p><p>This was a cross-sectional study involving a random sample of 2,002 men and women aged 46-73 years. Metabolic profiles and WC, hip circumference, pelvic width and body mass index (BMI) were determined. Correlation, logistic regression and area under the receiver operating characteristic curve analyses were used to evaluate obesity measurement relationships with metabolic risk phenotypes and type 2 diabetes.</p><p>Results</p><p>WC rib measures displayed the strongest associations with non-optimal lipid and lipoprotein levels, high blood pressure, insulin resistance, impaired fasting glucose, a clustering of metabolic risk features and type 2 diabetes, in both genders. Rib-derived indices improved discrimination of type 2 diabetes by 3-7% compared to BMI and 2-6% compared to WC midway (in men) and 5-7% compared to BMI and 4-6% compared to WC midway (in women). A prediction model including BMI and central obesity displayed a significantly higher area under the curve for WC rib (0.78, P=0.003), Rib/height ratio (0.80, P<0.001), Rib/pelvis ratio (0.79, P<0.001), but not for WC midway (0.75, P=0.127), when compared to one with BMI alone (0.74).</p><p>Conclusions</p><p>WC rib is easier to assess and our data suggest that it is a better method for determining obesity-related cardiometabolic risk than WC midway. The clinical utility of rib-derived indices, or alternative WC measurements, deserves further investigation.</p></div>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436493, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088", "stats"=>{"downloads"=>0, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Optimal_Central_Obesity_Measurement_Site_for_Assessing_Cardiometabolic_and_Type_2_Diabetes_Risk_in_Middle_Aged_Adults_/1436493", "title"=>"Optimal Central Obesity Measurement Site for Assessing Cardiometabolic and Type 2 Diabetes Risk in Middle-Aged Adults", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095469"], "description"=>"<p>Results are stratified by gender and adjusted for age.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436475, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g002", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Odds_ratios_95_CI_of_having_type_2_diabetes_for_a_one_standard_deviation_increase_in_each_obesity_measure_/1436475", "title"=>"Odds ratios (95% CI) of having type 2 diabetes for a one standard deviation increase in each obesity measure.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095492"], "description"=>"<p><sup>1</sup>All models include age and gender.</p><p><sup>2</sup>P value = 0.127 compared to model with BMI alone.</p><p><sup>3</sup>P value = 0.003 compared to model with BMI alone.</p><p><sup>4</sup>P value<0.001 compared to model with BMI alone.</p><p><sup>5</sup>P value<0.001 compared to model with BMI alone.</p><p>Tests of calibration, goodness-of-fit and discrimination for prediction models to identify subjects with type 2 diabetes.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436492, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.t003", "stats"=>{"downloads"=>5, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Tests_of_calibration_goodness_of_fit_and_discrimination_for_prediction_models_to_identify_subjects_with_type_2_diabetes_/1436492", "title"=>"Tests of calibration, goodness-of-fit and discrimination for prediction models to identify subjects with type 2 diabetes.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095489"], "description"=>"<p>Figures show ROC curves for a model including BMI and a model including BMI and Rib/pelvis ratio. All models include age and gender.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436489, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g009", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Receiver_operating_characteristic_curves_for_prediction_models_to_discriminate_subjects_with_type_2_diabetes_/1436489", "title"=>"Receiver operating characteristic curves for prediction models to discriminate subjects with type 2 diabetes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095487"], "description"=>"<p>Figures show ROC curves for a model including BMI and a model including BMI and Rib/height ratio. All models include age and gender.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436487, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g008", "stats"=>{"downloads"=>2, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Receiver_operating_characteristic_curves_for_prediction_models_to_discriminate_subjects_with_type_2_diabetes_/1436487", "title"=>"Receiver operating characteristic curves for prediction models to discriminate subjects with type 2 diabetes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095486"], "description"=>"<p>Figures show ROC curves for a model including BMI and a model including BMI and WC rib. All models include age and gender.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436486, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g007", "stats"=>{"downloads"=>3, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Receiver_operating_characteristic_curves_for_prediction_models_to_discriminate_subjects_with_type_2_diabetes_/1436486", "title"=>"Receiver operating characteristic curves for prediction models to discriminate subjects with type 2 diabetes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095477"], "description"=>"<p>Results are stratified by gender and adjusted for age. Bars represent false positive rates (percentages).</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436483, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g005", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_False_positive_rates_corresponding_to_90_80_70_and_60_sensitivities_for_selected_obesity_measures_to_classify_subjects_with_type_2_diabetes_/1436483", "title"=>"False positive rates corresponding to 90%, 80%, 70% and 60% sensitivities for selected obesity measures to classify subjects with type 2 diabetes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095471"], "description"=>"<p>Bars represent AUC values. All models exclude subjects with type 2 diabetes. Statistical differences in the AUC values are shown in superscript Arabic numbers as: <sup>1</sup>P<0.05 compared to WC midway; <sup>2</sup>P<0.05 compared to BMI.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436477, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g003", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Adjusted_area_under_the_receiver_operating_characteristic_curve_values_for_selected_obesity_measures_to_discriminate_subjects_with_three_or_more_cardiometabolic_risk_features_/1436477", "title"=>"Adjusted area under the receiver operating characteristic curve values for selected obesity measures to discriminate subjects with three or more cardiometabolic risk features.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095491"], "description"=>"<p><sup>1</sup>Adjusted for age.</p><p><sup>2</sup>nLog transformed.</p><p>All correlation coefficients are significant (P<0.05) except: <sup>3</sup>P>0.05. The index associated with the highest correlative strength to the variable in the same row is highlighted.</p><p>Partial correlations<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129088#t002fn001\" target=\"_blank\"><sup>1</sup></a> between anthropometric measurements and cardiometabolic variables, stratified by gender.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436491, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.t002", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Partial_correlations_1_between_anthropometric_measurements_and_cardiometabolic_variables_stratified_by_gender_/1436491", "title"=>"Partial correlations<sup>1</sup> between anthropometric measurements and cardiometabolic variables, stratified by gender.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095467"], "description"=>"<p>Results are stratified by gender and adjusted for age. All models exclude subjects with type 2 diabetes.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436473, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g001", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Odds_ratios_95_CI_of_having_three_or_more_cardiometabolic_risk_features_for_a_one_standard_deviation_increase_in_each_obesity_measure_/1436473", "title"=>"Odds ratios (95% CI) of having three or more cardiometabolic risk features for a one standard deviation increase in each obesity measure.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095490"], "description"=>"<p>Mean and ± standard deviation are shown for continuous variables, P value calculated with a Student’s <i>t</i>-test. Age, triglycerides, HOMA-IR, HbA<sub>1c</sub> and fasting plasma glucose are shown as a median (interquartile range) with a P value according to a Mann-Whitney U. % are shown for categorical values with <i>x</i><sup>2</sup> for difference in proportions, numbers and (%) may vary as some variables have missing values.</p><p><sup>1</sup>Triglycerides ≥1.7 mmol/l.</p><p><sup>2</sup>HDL-C <1.03 mmol/l (males) or HDL-C <1.29 mmol/l (females).</p><p><sup>3</sup>BP ≥130/85 mmHg or on Rx for hypertension.</p><p><sup>4</sup>HOMA-IR 75<sup>th</sup> percentile.</p><p><sup>5</sup>Excluding subjects with type 2 diabetes.</p><p><sup>6</sup>Fasting plasma glucose ≥5.6 mmol/l.</p><p>Characteristics of the study population.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436490, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.t001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characteristics_of_the_study_population_/1436490", "title"=>"Characteristics of the study population.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-04 03:02:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/2095485"], "description"=>"<p>Figures show ROC curves for a model including BMI and a model including BMI and WC midway. All models include age and gender.</p>", "links"=>[], "tags"=>["alternative WC measurements", "hip circumference", "Type 2 diabetes risk", "body mass index", "type 2 diabetes.ResultsWC rib measures", "lipoprotein levels", "measurement protocol", "bmi", "curve analyses", "prediction model", "Anthropometric variables", "Insulin resistance", "waist circumference", "risk phenotypes", "Optimal Central Obesity Measurement Site", "type 2 diabetes", "World Health Organisation", "obesity assessment", "International Diabetes Federation.Materials", "cardiometabolic health", "obesity measurement relationships", "Assessing Cardiometabolic", "risk features", "blood pressure", "fasting glucose", "Metabolic profiles", "cardiometabolic features", "measurement site influences", "WC rib"], "article_id"=>1436485, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Seán R. Millar", "Ivan J. Perry", "Jan Van den Broeck", "Catherine M. Phillips"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0129088.g006", "stats"=>{"downloads"=>1, "page_views"=>23, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Receiver_operating_characteristic_curves_for_prediction_models_to_discriminate_subjects_with_type_2_diabetes_/1436485", "title"=>"Receiver operating characteristic curves for prediction models to discriminate subjects with type 2 diabetes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-04 03:02:04"}

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  • {"unique-ip"=>"19", "full-text"=>"18", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"16", "full-text"=>"20", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"35", "full-text"=>"35", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"18", "full-text"=>"18", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"15", "full-text"=>"14", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"20", "full-text"=>"17", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"13", "full-text"=>"17", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"16", "full-text"=>"16", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"28", "full-text"=>"34", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"20", "full-text"=>"19", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"18", "full-text"=>"21", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"29", "full-text"=>"30", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"18", "full-text"=>"16", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"19", "full-text"=>"19", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"19", "full-text"=>"14", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}

Relative Metric

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