Application of three-dimensional body scanner: observation of prevalence of metabolic syndrome
Background & aims: This retrospective cross-sectional study correlates blood pressure, blood glucose, lipid and uric acid levels with anthropometric measurements. Methods: A total of 3975 visitors to the Department of Health Management were randomly selected to participate in this cross-sectiona...
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Veröffentlicht in: | Clinical nutrition (Edinburgh, Scotland) Scotland), 2004-12, Vol.23 (6), p.1313-1323 |
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description | Background & aims: This retrospective cross-sectional study correlates blood pressure, blood glucose, lipid and uric acid levels with anthropometric measurements.
Methods: A total of 3975 visitors to the Department of Health Management were randomly selected to participate in this cross-sectional study. Whole body three-dimensional (3-D) laser scans were used to obtain anthropometric measurements. A health index (HI) was also designed based on anthropometric parameters. Subjects were defined as having metabolic syndrome when three of the following criteria were met: obesity (BMI of at least 30kg/m2; or a WHR of over 0.9 for males and 0.85 for females); triglyceride of at least 150mg/dl; high-density lipoprotein (HDL)-cholesterol below 35mg/dl for males and 39mg/dl for females; fasting sugar levels of at least 110mg/dl and hypertension.
Results: Of 3975 subjects, 341 (8.6%) met the criteria for diabetes mellitus (DM); of these, 32.8% were diagnosed with hypertension. This proportion exceeded 18% of the subjects had normal glucose levels. Of the 3975 subjects, 658 (16.6%) met the criteria for metabolic syndrome. Proportionally, more male subjects than female subjects were diagnosed with metabolic syndrome (18.5% vs 14.7%). Of these, central obesity, elevated triglyceride and low HDL-cholesterol were the main factors in men, while fasting glucose, hypertension and central obesity were the main factors in women. This investigation found that larger proportions of subjects with impaired glucose tolerance (41.1%) and DM (64.2%) than of subjects with normal glucose subjects, suffered from metabolic syndrome (9.5%).
Conclusions: 3-D body scanning is useful in correlating pertinent factors with metabolic syndrome, these factors include central obesity, hyperglycemia, dyslipidemia, hyperuricemia and hypertension. |
doi_str_mv | 10.1016/j.clnu.2004.04.005 |
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Methods: A total of 3975 visitors to the Department of Health Management were randomly selected to participate in this cross-sectional study. Whole body three-dimensional (3-D) laser scans were used to obtain anthropometric measurements. A health index (HI) was also designed based on anthropometric parameters. Subjects were defined as having metabolic syndrome when three of the following criteria were met: obesity (BMI of at least 30kg/m2; or a WHR of over 0.9 for males and 0.85 for females); triglyceride of at least 150mg/dl; high-density lipoprotein (HDL)-cholesterol below 35mg/dl for males and 39mg/dl for females; fasting sugar levels of at least 110mg/dl and hypertension.
Results: Of 3975 subjects, 341 (8.6%) met the criteria for diabetes mellitus (DM); of these, 32.8% were diagnosed with hypertension. This proportion exceeded 18% of the subjects had normal glucose levels. Of the 3975 subjects, 658 (16.6%) met the criteria for metabolic syndrome. Proportionally, more male subjects than female subjects were diagnosed with metabolic syndrome (18.5% vs 14.7%). Of these, central obesity, elevated triglyceride and low HDL-cholesterol were the main factors in men, while fasting glucose, hypertension and central obesity were the main factors in women. This investigation found that larger proportions of subjects with impaired glucose tolerance (41.1%) and DM (64.2%) than of subjects with normal glucose subjects, suffered from metabolic syndrome (9.5%).
Conclusions: 3-D body scanning is useful in correlating pertinent factors with metabolic syndrome, these factors include central obesity, hyperglycemia, dyslipidemia, hyperuricemia and hypertension.</description><identifier>ISSN: 0261-5614</identifier><identifier>EISSN: 1532-1983</identifier><identifier>DOI: 10.1016/j.clnu.2004.04.005</identifier><identifier>PMID: 15556253</identifier><identifier>CODEN: CLNUDP</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Anthropometry ; Biological and medical sciences ; Blood Glucose - analysis ; Blood Glucose - metabolism ; Body Composition - physiology ; Body Constitution - physiology ; Body Mass Index ; Body mass index (BMI) ; Cholesterol, HDL - blood ; Cross-Sectional Studies ; Dyslipidemia ; Female ; Health index ; Health Status ; Health Status Indicators ; Health Surveys ; Humans ; Hyperlipidemias - blood ; Hyperlipidemias - complications ; Hyperlipidemias - diagnosis ; Hyperlipidemias - epidemiology ; Hypertension - complications ; Hypertension - diagnosis ; Hypertension - epidemiology ; Imaging, Three-Dimensional - methods ; Male ; Medical sciences ; Metabolic diseases ; Metabolic Syndrome - blood ; Metabolic Syndrome - diagnosis ; Metabolic Syndrome - epidemiology ; Middle Aged ; Miscellaneous ; Obesity - blood ; Obesity - complications ; Obesity - diagnosis ; Obesity - epidemiology ; Other metabolic disorders ; Prevalence ; Retrospective Studies ; Risk Factors ; Sex Factors ; Triglycerides - blood ; Uric Acid - blood ; Waist-Hip Ratio ; Waist/hip ratio (WHR)</subject><ispartof>Clinical nutrition (Edinburgh, Scotland), 2004-12, Vol.23 (6), p.1313-1323</ispartof><rights>2004 Elsevier Ltd</rights><rights>2005 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c382t-627980d72302c7c7d9244f466e59c288c01c91bf2f47cfe86df4948b0b7110193</citedby><cites>FETCH-LOGICAL-c382t-627980d72302c7c7d9244f466e59c288c01c91bf2f47cfe86df4948b0b7110193</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0261561404000639$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16319076$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15556253$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lin, J.D.</creatorcontrib><creatorcontrib>Chiou, W.K.</creatorcontrib><creatorcontrib>Weng, H.F.</creatorcontrib><creatorcontrib>Fang, J.T.</creatorcontrib><creatorcontrib>Liu, T.H.</creatorcontrib><title>Application of three-dimensional body scanner: observation of prevalence of metabolic syndrome</title><title>Clinical nutrition (Edinburgh, Scotland)</title><addtitle>Clin Nutr</addtitle><description>Background & aims: This retrospective cross-sectional study correlates blood pressure, blood glucose, lipid and uric acid levels with anthropometric measurements.
Methods: A total of 3975 visitors to the Department of Health Management were randomly selected to participate in this cross-sectional study. Whole body three-dimensional (3-D) laser scans were used to obtain anthropometric measurements. A health index (HI) was also designed based on anthropometric parameters. Subjects were defined as having metabolic syndrome when three of the following criteria were met: obesity (BMI of at least 30kg/m2; or a WHR of over 0.9 for males and 0.85 for females); triglyceride of at least 150mg/dl; high-density lipoprotein (HDL)-cholesterol below 35mg/dl for males and 39mg/dl for females; fasting sugar levels of at least 110mg/dl and hypertension.
Results: Of 3975 subjects, 341 (8.6%) met the criteria for diabetes mellitus (DM); of these, 32.8% were diagnosed with hypertension. This proportion exceeded 18% of the subjects had normal glucose levels. Of the 3975 subjects, 658 (16.6%) met the criteria for metabolic syndrome. Proportionally, more male subjects than female subjects were diagnosed with metabolic syndrome (18.5% vs 14.7%). Of these, central obesity, elevated triglyceride and low HDL-cholesterol were the main factors in men, while fasting glucose, hypertension and central obesity were the main factors in women. This investigation found that larger proportions of subjects with impaired glucose tolerance (41.1%) and DM (64.2%) than of subjects with normal glucose subjects, suffered from metabolic syndrome (9.5%).
Conclusions: 3-D body scanning is useful in correlating pertinent factors with metabolic syndrome, these factors include central obesity, hyperglycemia, dyslipidemia, hyperuricemia and hypertension.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Anthropometry</subject><subject>Biological and medical sciences</subject><subject>Blood Glucose - analysis</subject><subject>Blood Glucose - metabolism</subject><subject>Body Composition - physiology</subject><subject>Body Constitution - physiology</subject><subject>Body Mass Index</subject><subject>Body mass index (BMI)</subject><subject>Cholesterol, HDL - blood</subject><subject>Cross-Sectional Studies</subject><subject>Dyslipidemia</subject><subject>Female</subject><subject>Health index</subject><subject>Health Status</subject><subject>Health Status Indicators</subject><subject>Health Surveys</subject><subject>Humans</subject><subject>Hyperlipidemias - blood</subject><subject>Hyperlipidemias - complications</subject><subject>Hyperlipidemias - diagnosis</subject><subject>Hyperlipidemias - epidemiology</subject><subject>Hypertension - complications</subject><subject>Hypertension - diagnosis</subject><subject>Hypertension - epidemiology</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Metabolic diseases</subject><subject>Metabolic Syndrome - blood</subject><subject>Metabolic Syndrome - diagnosis</subject><subject>Metabolic Syndrome - epidemiology</subject><subject>Middle Aged</subject><subject>Miscellaneous</subject><subject>Obesity - blood</subject><subject>Obesity - complications</subject><subject>Obesity - diagnosis</subject><subject>Obesity - epidemiology</subject><subject>Other metabolic disorders</subject><subject>Prevalence</subject><subject>Retrospective Studies</subject><subject>Risk Factors</subject><subject>Sex Factors</subject><subject>Triglycerides - blood</subject><subject>Uric Acid - blood</subject><subject>Waist-Hip Ratio</subject><subject>Waist/hip ratio (WHR)</subject><issn>0261-5614</issn><issn>1532-1983</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kM1q3DAUhUVpSSbTvEAXxZtm54kk2_oJ3YSQPwh0024rZOmKarAlR_IMzNtHZoZkVzggJD6de_kQ-kbwhmDCrrcbM4TdhmLcbpbg7hNaka6hNZGi-YxWmDJSd4y05-gi5y0uRMPFGTonXdcx2jUr9Pd2mgZv9OxjqKKr5n8JoLZ-hJDLkx6qPtpDlY0OAdJNFfsMaf-OTwn2eoBgYLmNMOs-lroqH4JNcYSv6IvTQ4bL07lGfx7uf9891S-_Hp_vbl9q0wg614xyKbDltMHUcMOtpG3rWsagk4YKYTAxkvSOupYbB4JZ18pW9LjnpKiQzRpdHXunFF93kGc1-mxgGHSAuMuKcSwkJ6yA9AiaFHNO4NSU_KjTQRGsFqtqqxararGqlhRna_T91L7rR7AfX04aC_DjBOhianBJB-PzB8caIjFfpv88clBc7D0klY1f7FmfwMzKRv-_Pd4AwpmWFQ</recordid><startdate>20041201</startdate><enddate>20041201</enddate><creator>Lin, J.D.</creator><creator>Chiou, W.K.</creator><creator>Weng, H.F.</creator><creator>Fang, J.T.</creator><creator>Liu, T.H.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20041201</creationdate><title>Application of three-dimensional body scanner: observation of prevalence of metabolic syndrome</title><author>Lin, J.D. ; Chiou, W.K. ; Weng, H.F. ; Fang, J.T. ; Liu, T.H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c382t-627980d72302c7c7d9244f466e59c288c01c91bf2f47cfe86df4948b0b7110193</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Anthropometry</topic><topic>Biological and medical sciences</topic><topic>Blood Glucose - analysis</topic><topic>Blood Glucose - metabolism</topic><topic>Body Composition - physiology</topic><topic>Body Constitution - physiology</topic><topic>Body Mass Index</topic><topic>Body mass index (BMI)</topic><topic>Cholesterol, HDL - blood</topic><topic>Cross-Sectional Studies</topic><topic>Dyslipidemia</topic><topic>Female</topic><topic>Health index</topic><topic>Health Status</topic><topic>Health Status Indicators</topic><topic>Health Surveys</topic><topic>Humans</topic><topic>Hyperlipidemias - blood</topic><topic>Hyperlipidemias - complications</topic><topic>Hyperlipidemias - diagnosis</topic><topic>Hyperlipidemias - epidemiology</topic><topic>Hypertension - complications</topic><topic>Hypertension - diagnosis</topic><topic>Hypertension - epidemiology</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Metabolic diseases</topic><topic>Metabolic Syndrome - blood</topic><topic>Metabolic Syndrome - diagnosis</topic><topic>Metabolic Syndrome - epidemiology</topic><topic>Middle Aged</topic><topic>Miscellaneous</topic><topic>Obesity - blood</topic><topic>Obesity - complications</topic><topic>Obesity - diagnosis</topic><topic>Obesity - epidemiology</topic><topic>Other metabolic disorders</topic><topic>Prevalence</topic><topic>Retrospective Studies</topic><topic>Risk Factors</topic><topic>Sex Factors</topic><topic>Triglycerides - blood</topic><topic>Uric Acid - blood</topic><topic>Waist-Hip Ratio</topic><topic>Waist/hip ratio (WHR)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lin, J.D.</creatorcontrib><creatorcontrib>Chiou, W.K.</creatorcontrib><creatorcontrib>Weng, H.F.</creatorcontrib><creatorcontrib>Fang, J.T.</creatorcontrib><creatorcontrib>Liu, T.H.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical nutrition (Edinburgh, Scotland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, J.D.</au><au>Chiou, W.K.</au><au>Weng, H.F.</au><au>Fang, J.T.</au><au>Liu, T.H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of three-dimensional body scanner: observation of prevalence of metabolic syndrome</atitle><jtitle>Clinical nutrition (Edinburgh, Scotland)</jtitle><addtitle>Clin Nutr</addtitle><date>2004-12-01</date><risdate>2004</risdate><volume>23</volume><issue>6</issue><spage>1313</spage><epage>1323</epage><pages>1313-1323</pages><issn>0261-5614</issn><eissn>1532-1983</eissn><coden>CLNUDP</coden><abstract>Background & aims: This retrospective cross-sectional study correlates blood pressure, blood glucose, lipid and uric acid levels with anthropometric measurements.
Methods: A total of 3975 visitors to the Department of Health Management were randomly selected to participate in this cross-sectional study. Whole body three-dimensional (3-D) laser scans were used to obtain anthropometric measurements. A health index (HI) was also designed based on anthropometric parameters. Subjects were defined as having metabolic syndrome when three of the following criteria were met: obesity (BMI of at least 30kg/m2; or a WHR of over 0.9 for males and 0.85 for females); triglyceride of at least 150mg/dl; high-density lipoprotein (HDL)-cholesterol below 35mg/dl for males and 39mg/dl for females; fasting sugar levels of at least 110mg/dl and hypertension.
Results: Of 3975 subjects, 341 (8.6%) met the criteria for diabetes mellitus (DM); of these, 32.8% were diagnosed with hypertension. This proportion exceeded 18% of the subjects had normal glucose levels. Of the 3975 subjects, 658 (16.6%) met the criteria for metabolic syndrome. Proportionally, more male subjects than female subjects were diagnosed with metabolic syndrome (18.5% vs 14.7%). Of these, central obesity, elevated triglyceride and low HDL-cholesterol were the main factors in men, while fasting glucose, hypertension and central obesity were the main factors in women. This investigation found that larger proportions of subjects with impaired glucose tolerance (41.1%) and DM (64.2%) than of subjects with normal glucose subjects, suffered from metabolic syndrome (9.5%).
Conclusions: 3-D body scanning is useful in correlating pertinent factors with metabolic syndrome, these factors include central obesity, hyperglycemia, dyslipidemia, hyperuricemia and hypertension.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>15556253</pmid><doi>10.1016/j.clnu.2004.04.005</doi><tpages>11</tpages></addata></record> |
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subjects | Adult Aged Aged, 80 and over Anthropometry Biological and medical sciences Blood Glucose - analysis Blood Glucose - metabolism Body Composition - physiology Body Constitution - physiology Body Mass Index Body mass index (BMI) Cholesterol, HDL - blood Cross-Sectional Studies Dyslipidemia Female Health index Health Status Health Status Indicators Health Surveys Humans Hyperlipidemias - blood Hyperlipidemias - complications Hyperlipidemias - diagnosis Hyperlipidemias - epidemiology Hypertension - complications Hypertension - diagnosis Hypertension - epidemiology Imaging, Three-Dimensional - methods Male Medical sciences Metabolic diseases Metabolic Syndrome - blood Metabolic Syndrome - diagnosis Metabolic Syndrome - epidemiology Middle Aged Miscellaneous Obesity - blood Obesity - complications Obesity - diagnosis Obesity - epidemiology Other metabolic disorders Prevalence Retrospective Studies Risk Factors Sex Factors Triglycerides - blood Uric Acid - blood Waist-Hip Ratio Waist/hip ratio (WHR) |
title | Application of three-dimensional body scanner: observation of prevalence of metabolic syndrome |
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