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Predictive power of a body shape index for development of diabetes, hypertension, and dyslipidemia in Japanese adults: a retrospective cohort study
Recently, a body shape index (ABSI) was reported to predict all-cause mortality independently of body mass index (BMI) in Americans. This study aimed to evaluate whether ABSI is applicable to Japanese adults as a predictor for development of diabetes, hypertension, and dyslipidemia. We evaluated the...
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Published in: | PloS one 2015-06, Vol.10 (6), p.e0128972-e0128972 |
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description | Recently, a body shape index (ABSI) was reported to predict all-cause mortality independently of body mass index (BMI) in Americans. This study aimed to evaluate whether ABSI is applicable to Japanese adults as a predictor for development of diabetes, hypertension, and dyslipidemia.
We evaluated the predictive power of ABSI in a retrospective cohort study using annual health examination data from Chiba City Hall in Japan, for the period 2008 to 2012. Subjects included 37,581 without diabetes, 23,090 without hypertension, and 20,776 without dyslipidemia at baseline who were monitored for disease incidence for 4 years. We examined the associations of standardized ABSI, BMI, and waist circumference (WC) at baseline with disease incidence by logistic regression analyses. Furthermore, we conducted a case-matched study using the propensity score matching method.
Elevated BMI, WC, and ABSI increased the risks of diabetes and dyslipidemia [BMI-diabetes: odds ratio (OR) = 1.26, 95% confidence interval (95%CI) = 1.20-1.32; BMI-dyslipidemia: OR = 1.15, 95%CI = 1.12-1.19; WC-diabetes: OR = 1.24, 95%CI = 1.18-1.31; WC-dyslipidemia: OR = 1.15, 95%CI = 1.11-1.19; ABSI-diabetes: OR = 1.06, 95%CI = 1.01-1.11; ABSI-dyslipidemia: OR = 1.04, 95%CI = 1.01-1.07]. Elevated BMI and WC, but not higher ABSI, also increased the risk of hypertension [BMI: OR = 1.32, 95%CI = 1.27-1.37; WC: OR = 1.22, 95%CI = 1.18-1.26; ABSI: OR = 1.00, 95%CI = 0.97-1.02]. Areas under the curve (AUCs) in regression models with ABSI were significantly smaller than in models with BMI or WC for all three diseases. In case-matched subgroups, the power of ABSI was weaker than that of BMI and WC for predicting the incidence of diabetes, hypertension, and dyslipidemia.
Compared with BMI or WC, ABSI was not a better predictor of diabetes, hypertension, and dyslipidemia in Japanese adults. |
doi_str_mv | 10.1371/journal.pone.0128972 |
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We evaluated the predictive power of ABSI in a retrospective cohort study using annual health examination data from Chiba City Hall in Japan, for the period 2008 to 2012. Subjects included 37,581 without diabetes, 23,090 without hypertension, and 20,776 without dyslipidemia at baseline who were monitored for disease incidence for 4 years. We examined the associations of standardized ABSI, BMI, and waist circumference (WC) at baseline with disease incidence by logistic regression analyses. Furthermore, we conducted a case-matched study using the propensity score matching method.
Elevated BMI, WC, and ABSI increased the risks of diabetes and dyslipidemia [BMI-diabetes: odds ratio (OR) = 1.26, 95% confidence interval (95%CI) = 1.20-1.32; BMI-dyslipidemia: OR = 1.15, 95%CI = 1.12-1.19; WC-diabetes: OR = 1.24, 95%CI = 1.18-1.31; WC-dyslipidemia: OR = 1.15, 95%CI = 1.11-1.19; ABSI-diabetes: OR = 1.06, 95%CI = 1.01-1.11; ABSI-dyslipidemia: OR = 1.04, 95%CI = 1.01-1.07]. Elevated BMI and WC, but not higher ABSI, also increased the risk of hypertension [BMI: OR = 1.32, 95%CI = 1.27-1.37; WC: OR = 1.22, 95%CI = 1.18-1.26; ABSI: OR = 1.00, 95%CI = 0.97-1.02]. Areas under the curve (AUCs) in regression models with ABSI were significantly smaller than in models with BMI or WC for all three diseases. In case-matched subgroups, the power of ABSI was weaker than that of BMI and WC for predicting the incidence of diabetes, hypertension, and dyslipidemia.
Compared with BMI or WC, ABSI was not a better predictor of diabetes, hypertension, and dyslipidemia in Japanese adults.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0128972</identifier><identifier>PMID: 26030122</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Abdomen ; Adults ; Analysis ; Asian People ; Atherosclerosis ; Body mass ; Body Mass Index ; Body size ; Cohort analysis ; Committees ; Confidence intervals ; Diabetes ; Diabetes mellitus ; Dyslipidemia ; Dyslipidemias - etiology ; Fasting ; Female ; Health risk assessment ; Health risks ; Hemodialysis ; Hospitals ; Humans ; Hypertension ; Hypertension - etiology ; Incidence ; Japan ; Male ; Medical examination ; Metabolic disorders ; Metabolism ; Middle Aged ; Mortality ; Obesity ; Obesity - etiology ; Population ; Prognosis ; Public health ; Regression analysis ; Regression models ; Retrospective Studies ; Risk Factors ; Statistical analysis ; Studies ; Subgroups ; Systematic review ; Waist Circumference - physiology ; Womens health</subject><ispartof>PloS one, 2015-06, Vol.10 (6), p.e0128972-e0128972</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Fujita et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Fujita et al 2015 Fujita et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c758t-71435906565820f330d5c0827b55edfc764d5d0506fc47e643877affb3ea16833</citedby><cites>FETCH-LOGICAL-c758t-71435906565820f330d5c0827b55edfc764d5d0506fc47e643877affb3ea16833</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1684995376/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1684995376?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26030122$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Taheri, Shahrad</contributor><creatorcontrib>Fujita, Misuzu</creatorcontrib><creatorcontrib>Sato, Yasunori</creatorcontrib><creatorcontrib>Nagashima, Kengo</creatorcontrib><creatorcontrib>Takahashi, Sho</creatorcontrib><creatorcontrib>Hata, Akira</creatorcontrib><title>Predictive power of a body shape index for development of diabetes, hypertension, and dyslipidemia in Japanese adults: a retrospective cohort study</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Recently, a body shape index (ABSI) was reported to predict all-cause mortality independently of body mass index (BMI) in Americans. This study aimed to evaluate whether ABSI is applicable to Japanese adults as a predictor for development of diabetes, hypertension, and dyslipidemia.
We evaluated the predictive power of ABSI in a retrospective cohort study using annual health examination data from Chiba City Hall in Japan, for the period 2008 to 2012. Subjects included 37,581 without diabetes, 23,090 without hypertension, and 20,776 without dyslipidemia at baseline who were monitored for disease incidence for 4 years. We examined the associations of standardized ABSI, BMI, and waist circumference (WC) at baseline with disease incidence by logistic regression analyses. Furthermore, we conducted a case-matched study using the propensity score matching method.
Elevated BMI, WC, and ABSI increased the risks of diabetes and dyslipidemia [BMI-diabetes: odds ratio (OR) = 1.26, 95% confidence interval (95%CI) = 1.20-1.32; BMI-dyslipidemia: OR = 1.15, 95%CI = 1.12-1.19; WC-diabetes: OR = 1.24, 95%CI = 1.18-1.31; WC-dyslipidemia: OR = 1.15, 95%CI = 1.11-1.19; ABSI-diabetes: OR = 1.06, 95%CI = 1.01-1.11; ABSI-dyslipidemia: OR = 1.04, 95%CI = 1.01-1.07]. Elevated BMI and WC, but not higher ABSI, also increased the risk of hypertension [BMI: OR = 1.32, 95%CI = 1.27-1.37; WC: OR = 1.22, 95%CI = 1.18-1.26; ABSI: OR = 1.00, 95%CI = 0.97-1.02]. Areas under the curve (AUCs) in regression models with ABSI were significantly smaller than in models with BMI or WC for all three diseases. In case-matched subgroups, the power of ABSI was weaker than that of BMI and WC for predicting the incidence of diabetes, hypertension, and dyslipidemia.
Compared with BMI or WC, ABSI was not a better predictor of diabetes, hypertension, and dyslipidemia in Japanese adults.</description><subject>Abdomen</subject><subject>Adults</subject><subject>Analysis</subject><subject>Asian People</subject><subject>Atherosclerosis</subject><subject>Body mass</subject><subject>Body Mass Index</subject><subject>Body size</subject><subject>Cohort analysis</subject><subject>Committees</subject><subject>Confidence intervals</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Dyslipidemia</subject><subject>Dyslipidemias - etiology</subject><subject>Fasting</subject><subject>Female</subject><subject>Health risk assessment</subject><subject>Health risks</subject><subject>Hemodialysis</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Hypertension - etiology</subject><subject>Incidence</subject><subject>Japan</subject><subject>Male</subject><subject>Medical examination</subject><subject>Metabolic disorders</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Obesity</subject><subject>Obesity - etiology</subject><subject>Population</subject><subject>Prognosis</subject><subject>Public health</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Retrospective Studies</subject><subject>Risk Factors</subject><subject>Statistical analysis</subject><subject>Studies</subject><subject>Subgroups</subject><subject>Systematic review</subject><subject>Waist Circumference - physiology</subject><subject>Womens health</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNk11v0zAUhiMEYqPwDxBYQkIgrcWxYzvlAmma-CiaNMTXreXYJ42nNA62U9bfwR_GXbOpRbtAvohjP-c99utzsuxpjmc5FfmbSzf4TrWz3nUwwzkp54Lcy47zOSVTTjC9vzc_yh6FcIkxoyXnD7MjwjFNIeQ4-_PFg7E62jWg3v0Gj1yNFKqc2aDQqB6Q7Qxcodp5ZGANretX0MUtZayqIEI4Qc2mBx-hC9Z1J0h1BplNaG1vDaysSgros-pVBwGQMkMbw9uUwkP0LvSwy61d43xEIQ5m8zh7UKs2wJPxO8l-fHj__ezT9Pzi4-Ls9HyqBSvjVOQFZXPMGWclwTWl2DCNSyIqxsDUWvDCMIMZ5rUuBPCClkKouq4oqJyXlE6y5zvdvnVBjn4GmfaK-ZxRwROx2BHGqUvZe7tSfiOdsvJ6wfmlVD5a3YIUFHOi64LSnBTAqiqdjjJCckYM1ulnkr0bsw3VCoxOLnrVHoge7nS2kUu3lkXBcsHnSeDVKODdrwFClCsbNLRtctYN1-dmIplBt-iLf9C7bzdSS5UuYLvapbx6KypPC0JLyjjJEzW7g0pj-7g6FV9t0_pBwOuDgMREuIpLNYQgF9--_j978fOQfbnHNqDa2ATXDjFVXTgEix2oU4EFD_WtyTmW2965cUNue0eOvZPCnu0_0G3QTbPQv2C8FEg</recordid><startdate>20150601</startdate><enddate>20150601</enddate><creator>Fujita, Misuzu</creator><creator>Sato, Yasunori</creator><creator>Nagashima, Kengo</creator><creator>Takahashi, Sho</creator><creator>Hata, Akira</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20150601</creationdate><title>Predictive power of a body shape index for development of diabetes, hypertension, and dyslipidemia in Japanese adults: a retrospective cohort study</title><author>Fujita, Misuzu ; Sato, Yasunori ; Nagashima, Kengo ; Takahashi, Sho ; Hata, Akira</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c758t-71435906565820f330d5c0827b55edfc764d5d0506fc47e643877affb3ea16833</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Abdomen</topic><topic>Adults</topic><topic>Analysis</topic><topic>Asian People</topic><topic>Atherosclerosis</topic><topic>Body mass</topic><topic>Body Mass Index</topic><topic>Body size</topic><topic>Cohort analysis</topic><topic>Committees</topic><topic>Confidence intervals</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Dyslipidemia</topic><topic>Dyslipidemias - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fujita, Misuzu</au><au>Sato, Yasunori</au><au>Nagashima, Kengo</au><au>Takahashi, Sho</au><au>Hata, Akira</au><au>Taheri, Shahrad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predictive power of a body shape index for development of diabetes, hypertension, and dyslipidemia in Japanese adults: a retrospective cohort study</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2015-06-01</date><risdate>2015</risdate><volume>10</volume><issue>6</issue><spage>e0128972</spage><epage>e0128972</epage><pages>e0128972-e0128972</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Recently, a body shape index (ABSI) was reported to predict all-cause mortality independently of body mass index (BMI) in Americans. This study aimed to evaluate whether ABSI is applicable to Japanese adults as a predictor for development of diabetes, hypertension, and dyslipidemia.
We evaluated the predictive power of ABSI in a retrospective cohort study using annual health examination data from Chiba City Hall in Japan, for the period 2008 to 2012. Subjects included 37,581 without diabetes, 23,090 without hypertension, and 20,776 without dyslipidemia at baseline who were monitored for disease incidence for 4 years. We examined the associations of standardized ABSI, BMI, and waist circumference (WC) at baseline with disease incidence by logistic regression analyses. Furthermore, we conducted a case-matched study using the propensity score matching method.
Elevated BMI, WC, and ABSI increased the risks of diabetes and dyslipidemia [BMI-diabetes: odds ratio (OR) = 1.26, 95% confidence interval (95%CI) = 1.20-1.32; BMI-dyslipidemia: OR = 1.15, 95%CI = 1.12-1.19; WC-diabetes: OR = 1.24, 95%CI = 1.18-1.31; WC-dyslipidemia: OR = 1.15, 95%CI = 1.11-1.19; ABSI-diabetes: OR = 1.06, 95%CI = 1.01-1.11; ABSI-dyslipidemia: OR = 1.04, 95%CI = 1.01-1.07]. Elevated BMI and WC, but not higher ABSI, also increased the risk of hypertension [BMI: OR = 1.32, 95%CI = 1.27-1.37; WC: OR = 1.22, 95%CI = 1.18-1.26; ABSI: OR = 1.00, 95%CI = 0.97-1.02]. Areas under the curve (AUCs) in regression models with ABSI were significantly smaller than in models with BMI or WC for all three diseases. In case-matched subgroups, the power of ABSI was weaker than that of BMI and WC for predicting the incidence of diabetes, hypertension, and dyslipidemia.
Compared with BMI or WC, ABSI was not a better predictor of diabetes, hypertension, and dyslipidemia in Japanese adults.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26030122</pmid><doi>10.1371/journal.pone.0128972</doi><oa>free_for_read</oa></addata></record> |
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source | Open Access: PubMed Central; ProQuest - Publicly Available Content Database |
subjects | Abdomen Adults Analysis Asian People Atherosclerosis Body mass Body Mass Index Body size Cohort analysis Committees Confidence intervals Diabetes Diabetes mellitus Dyslipidemia Dyslipidemias - etiology Fasting Female Health risk assessment Health risks Hemodialysis Hospitals Humans Hypertension Hypertension - etiology Incidence Japan Male Medical examination Metabolic disorders Metabolism Middle Aged Mortality Obesity Obesity - etiology Population Prognosis Public health Regression analysis Regression models Retrospective Studies Risk Factors Statistical analysis Studies Subgroups Systematic review Waist Circumference - physiology Womens health |
title | Predictive power of a body shape index for development of diabetes, hypertension, and dyslipidemia in Japanese adults: a retrospective cohort study |
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