Loading…

Prevalence and Clinical Profile of Metabolic Obesity and Phenotypic Obesity in Asian Indians

Background: We estimated the prevalence of metabolically obese nonobese (MONO), metabolically obese obese (MOO), and metabolically healthy obese (MHO) individuals and correlated this with the prevalence of coronary artery disease (CAD) compared to metabolically healthy nonobese (MHNO) in urban South...

Full description

Saved in:
Bibliographic Details
Published in:Journal of diabetes science and technology 2011-03, Vol.5 (2), p.439-446
Main Authors: Geetha, Loganathan, Deepa, Mohan, Anjana, Ranjit Mohan, Mohan, Viswanathan
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c4225-11f4bfa79b09b7769aac121064f591f39d915a5ac1ce7b6801f18b7537b6ec963
cites cdi_FETCH-LOGICAL-c4225-11f4bfa79b09b7769aac121064f591f39d915a5ac1ce7b6801f18b7537b6ec963
container_end_page 446
container_issue 2
container_start_page 439
container_title Journal of diabetes science and technology
container_volume 5
creator Geetha, Loganathan
Deepa, Mohan
Anjana, Ranjit Mohan
Mohan, Viswanathan
description Background: We estimated the prevalence of metabolically obese nonobese (MONO), metabolically obese obese (MOO), and metabolically healthy obese (MHO) individuals and correlated this with the prevalence of coronary artery disease (CAD) compared to metabolically healthy nonobese (MHNO) in urban South Indians. Method: Study subjects (n = 2350) were recruited from the Chennai Urban Rural Epidemiology Study. Generalized obesity was defined as a body mass index (BMI) ≥25 kg/m2, based on the World Health Organization Asia Pacific guidelines. Metabolic syndrome (MS) was diagnosed based on the South Asian Modified-National Cholesterol Education Programme criteria. Coronary artery disease was defined by known myocardial infarction or Q waves on resting electrocardiogram. Results: Metabolically obese nonobese was defined as nonobese subjects (BMI < 25 kg/m2) with MS, MOO as obesity (BMI = 25 kg/m2) with MS, MHO as obese subjects (BMI = 25 kg/m2) with no MS, and MHNO as no obesity or MS. Metabolically obese nonobese was identified in 355 (15.1%), MOO in 348 (14.8%), MHO in 312 (13.3%), and MHNO in 1335 (56.8%) subjects. The prevalence of CAD among the MONO, MOO, MHO, and MHNO was 5.5%, 4.2%, 1.4%, and 2.6%. However, when age standardization was done, there was no statistically significant increase in the risk of CAD among MONO [odds ratio (OR) = 1.300, 95% confidence interval (CI) 0.706–2.394, p = .339], MOO (OR = 1.651, 95% CI 0.852–3.199, p = .137), and MHO (OR = 0.524, 95% CI 0.250–2.130, p = .564) groups compared to MHNO, perhaps due to small numbers. Conclusion: Metabolic obesity may have different clinical implications than phenotypic obesity.
doi_str_mv 10.1177/193229681100500235
format article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3125940</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_193229681100500235</sage_id><sourcerecordid>864193058</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4225-11f4bfa79b09b7769aac121064f591f39d915a5ac1ce7b6801f18b7537b6ec963</originalsourceid><addsrcrecordid>eNp9kUFPGzEQhS1UBDTlD3Co9tZTGo93vV5fKqGItkhB5AC3SpbXGQcjx07tDVL-fR0CKBUSp7Gfv3ljzSPkAuh3ACEmIGvGZNsBUMopZTU_Imc7cbxTPx2cT8nnnB8L1XRCnJBTBpyJ4nFG_swTPmmPwWClw6Kaehec0b6ap2idxyra6gYH3UfvTHXbY3bD9pmcP2CIw3Z9ILtQXWanQ3UdFqXkL-TYap_x_KWOyP3Pq7vp7_Hs9tf19HI2Ng1jfAxgm95qIXsqeyFaqbUBBrRtLJdga7mQwDUvokHRtx0FC10veF0uaGRbj8iPve96069wYTAMSXu1Tm6l01ZF7dT_L8E9qGV8UjUwLhtaDL69GKT4d4N5UCuXDXqvA8ZNVl3blF1S3hWS7UmTYs4J7dsUoGqXinqfSmn6evi_t5bXGAow2QNZL1E9xk0KZV8fWf4DFgqVhA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>864193058</pqid></control><display><type>article</type><title>Prevalence and Clinical Profile of Metabolic Obesity and Phenotypic Obesity in Asian Indians</title><source>SAGE:Jisc Collections:SAGE Journals Read and Publish 2023-2024:2025 extension (reading list)</source><source>PubMed Central</source><creator>Geetha, Loganathan ; Deepa, Mohan ; Anjana, Ranjit Mohan ; Mohan, Viswanathan</creator><creatorcontrib>Geetha, Loganathan ; Deepa, Mohan ; Anjana, Ranjit Mohan ; Mohan, Viswanathan</creatorcontrib><description>Background: We estimated the prevalence of metabolically obese nonobese (MONO), metabolically obese obese (MOO), and metabolically healthy obese (MHO) individuals and correlated this with the prevalence of coronary artery disease (CAD) compared to metabolically healthy nonobese (MHNO) in urban South Indians. Method: Study subjects (n = 2350) were recruited from the Chennai Urban Rural Epidemiology Study. Generalized obesity was defined as a body mass index (BMI) ≥25 kg/m2, based on the World Health Organization Asia Pacific guidelines. Metabolic syndrome (MS) was diagnosed based on the South Asian Modified-National Cholesterol Education Programme criteria. Coronary artery disease was defined by known myocardial infarction or Q waves on resting electrocardiogram. Results: Metabolically obese nonobese was defined as nonobese subjects (BMI &lt; 25 kg/m2) with MS, MOO as obesity (BMI = 25 kg/m2) with MS, MHO as obese subjects (BMI = 25 kg/m2) with no MS, and MHNO as no obesity or MS. Metabolically obese nonobese was identified in 355 (15.1%), MOO in 348 (14.8%), MHO in 312 (13.3%), and MHNO in 1335 (56.8%) subjects. The prevalence of CAD among the MONO, MOO, MHO, and MHNO was 5.5%, 4.2%, 1.4%, and 2.6%. However, when age standardization was done, there was no statistically significant increase in the risk of CAD among MONO [odds ratio (OR) = 1.300, 95% confidence interval (CI) 0.706–2.394, p = .339], MOO (OR = 1.651, 95% CI 0.852–3.199, p = .137), and MHO (OR = 0.524, 95% CI 0.250–2.130, p = .564) groups compared to MHNO, perhaps due to small numbers. Conclusion: Metabolic obesity may have different clinical implications than phenotypic obesity.</description><identifier>ISSN: 1932-2968</identifier><identifier>EISSN: 1932-2968</identifier><identifier>EISSN: 1932-3107</identifier><identifier>DOI: 10.1177/193229681100500235</identifier><identifier>PMID: 21527117</identifier><language>eng</language><publisher>United States: SAGE Publications</publisher><subject>Adult ; Anthropometry ; Blood Glucose - analysis ; Body Mass Index ; Cholesterol, LDL - metabolism ; Coronary Artery Disease - blood ; Cross-Sectional Studies ; Female ; Glucose Tolerance Test ; Humans ; Hypertension - blood ; Hypertriglyceridemia - blood ; India ; Male ; Metabolic Syndrome - blood ; Middle Aged ; Models, Statistical ; Obesity - blood ; Obesity - complications ; Obesity - epidemiology ; Obesity - metabolism ; Obesity Technology ; Prevalence</subject><ispartof>Journal of diabetes science and technology, 2011-03, Vol.5 (2), p.439-446</ispartof><rights>2011 Diabetes Technology Society</rights><rights>2011 Diabetes Technology Society.</rights><rights>2011 Diabetes Technology Society 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4225-11f4bfa79b09b7769aac121064f591f39d915a5ac1ce7b6801f18b7537b6ec963</citedby><cites>FETCH-LOGICAL-c4225-11f4bfa79b09b7769aac121064f591f39d915a5ac1ce7b6801f18b7537b6ec963</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3125940/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3125940/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21527117$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Geetha, Loganathan</creatorcontrib><creatorcontrib>Deepa, Mohan</creatorcontrib><creatorcontrib>Anjana, Ranjit Mohan</creatorcontrib><creatorcontrib>Mohan, Viswanathan</creatorcontrib><title>Prevalence and Clinical Profile of Metabolic Obesity and Phenotypic Obesity in Asian Indians</title><title>Journal of diabetes science and technology</title><addtitle>J Diabetes Sci Technol</addtitle><description>Background: We estimated the prevalence of metabolically obese nonobese (MONO), metabolically obese obese (MOO), and metabolically healthy obese (MHO) individuals and correlated this with the prevalence of coronary artery disease (CAD) compared to metabolically healthy nonobese (MHNO) in urban South Indians. Method: Study subjects (n = 2350) were recruited from the Chennai Urban Rural Epidemiology Study. Generalized obesity was defined as a body mass index (BMI) ≥25 kg/m2, based on the World Health Organization Asia Pacific guidelines. Metabolic syndrome (MS) was diagnosed based on the South Asian Modified-National Cholesterol Education Programme criteria. Coronary artery disease was defined by known myocardial infarction or Q waves on resting electrocardiogram. Results: Metabolically obese nonobese was defined as nonobese subjects (BMI &lt; 25 kg/m2) with MS, MOO as obesity (BMI = 25 kg/m2) with MS, MHO as obese subjects (BMI = 25 kg/m2) with no MS, and MHNO as no obesity or MS. Metabolically obese nonobese was identified in 355 (15.1%), MOO in 348 (14.8%), MHO in 312 (13.3%), and MHNO in 1335 (56.8%) subjects. The prevalence of CAD among the MONO, MOO, MHO, and MHNO was 5.5%, 4.2%, 1.4%, and 2.6%. However, when age standardization was done, there was no statistically significant increase in the risk of CAD among MONO [odds ratio (OR) = 1.300, 95% confidence interval (CI) 0.706–2.394, p = .339], MOO (OR = 1.651, 95% CI 0.852–3.199, p = .137), and MHO (OR = 0.524, 95% CI 0.250–2.130, p = .564) groups compared to MHNO, perhaps due to small numbers. Conclusion: Metabolic obesity may have different clinical implications than phenotypic obesity.</description><subject>Adult</subject><subject>Anthropometry</subject><subject>Blood Glucose - analysis</subject><subject>Body Mass Index</subject><subject>Cholesterol, LDL - metabolism</subject><subject>Coronary Artery Disease - blood</subject><subject>Cross-Sectional Studies</subject><subject>Female</subject><subject>Glucose Tolerance Test</subject><subject>Humans</subject><subject>Hypertension - blood</subject><subject>Hypertriglyceridemia - blood</subject><subject>India</subject><subject>Male</subject><subject>Metabolic Syndrome - blood</subject><subject>Middle Aged</subject><subject>Models, Statistical</subject><subject>Obesity - blood</subject><subject>Obesity - complications</subject><subject>Obesity - epidemiology</subject><subject>Obesity - metabolism</subject><subject>Obesity Technology</subject><subject>Prevalence</subject><issn>1932-2968</issn><issn>1932-2968</issn><issn>1932-3107</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNp9kUFPGzEQhS1UBDTlD3Co9tZTGo93vV5fKqGItkhB5AC3SpbXGQcjx07tDVL-fR0CKBUSp7Gfv3ljzSPkAuh3ACEmIGvGZNsBUMopZTU_Imc7cbxTPx2cT8nnnB8L1XRCnJBTBpyJ4nFG_swTPmmPwWClw6Kaehec0b6ap2idxyra6gYH3UfvTHXbY3bD9pmcP2CIw3Z9ILtQXWanQ3UdFqXkL-TYap_x_KWOyP3Pq7vp7_Hs9tf19HI2Ng1jfAxgm95qIXsqeyFaqbUBBrRtLJdga7mQwDUvokHRtx0FC10veF0uaGRbj8iPve96069wYTAMSXu1Tm6l01ZF7dT_L8E9qGV8UjUwLhtaDL69GKT4d4N5UCuXDXqvA8ZNVl3blF1S3hWS7UmTYs4J7dsUoGqXinqfSmn6evi_t5bXGAow2QNZL1E9xk0KZV8fWf4DFgqVhA</recordid><startdate>201103</startdate><enddate>201103</enddate><creator>Geetha, Loganathan</creator><creator>Deepa, Mohan</creator><creator>Anjana, Ranjit Mohan</creator><creator>Mohan, Viswanathan</creator><general>SAGE Publications</general><general>Diabetes Technology Society</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>7X8</scope><scope>5PM</scope></search><sort><creationdate>201103</creationdate><title>Prevalence and Clinical Profile of Metabolic Obesity and Phenotypic Obesity in Asian Indians</title><author>Geetha, Loganathan ; Deepa, Mohan ; Anjana, Ranjit Mohan ; Mohan, Viswanathan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4225-11f4bfa79b09b7769aac121064f591f39d915a5ac1ce7b6801f18b7537b6ec963</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Adult</topic><topic>Anthropometry</topic><topic>Blood Glucose - analysis</topic><topic>Body Mass Index</topic><topic>Cholesterol, LDL - metabolism</topic><topic>Coronary Artery Disease - blood</topic><topic>Cross-Sectional Studies</topic><topic>Female</topic><topic>Glucose Tolerance Test</topic><topic>Humans</topic><topic>Hypertension - blood</topic><topic>Hypertriglyceridemia - blood</topic><topic>India</topic><topic>Male</topic><topic>Metabolic Syndrome - blood</topic><topic>Middle Aged</topic><topic>Models, Statistical</topic><topic>Obesity - blood</topic><topic>Obesity - complications</topic><topic>Obesity - epidemiology</topic><topic>Obesity - metabolism</topic><topic>Obesity Technology</topic><topic>Prevalence</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Geetha, Loganathan</creatorcontrib><creatorcontrib>Deepa, Mohan</creatorcontrib><creatorcontrib>Anjana, Ranjit Mohan</creatorcontrib><creatorcontrib>Mohan, Viswanathan</creatorcontrib><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><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of diabetes science and technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Geetha, Loganathan</au><au>Deepa, Mohan</au><au>Anjana, Ranjit Mohan</au><au>Mohan, Viswanathan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prevalence and Clinical Profile of Metabolic Obesity and Phenotypic Obesity in Asian Indians</atitle><jtitle>Journal of diabetes science and technology</jtitle><addtitle>J Diabetes Sci Technol</addtitle><date>2011-03</date><risdate>2011</risdate><volume>5</volume><issue>2</issue><spage>439</spage><epage>446</epage><pages>439-446</pages><issn>1932-2968</issn><eissn>1932-2968</eissn><eissn>1932-3107</eissn><abstract>Background: We estimated the prevalence of metabolically obese nonobese (MONO), metabolically obese obese (MOO), and metabolically healthy obese (MHO) individuals and correlated this with the prevalence of coronary artery disease (CAD) compared to metabolically healthy nonobese (MHNO) in urban South Indians. Method: Study subjects (n = 2350) were recruited from the Chennai Urban Rural Epidemiology Study. Generalized obesity was defined as a body mass index (BMI) ≥25 kg/m2, based on the World Health Organization Asia Pacific guidelines. Metabolic syndrome (MS) was diagnosed based on the South Asian Modified-National Cholesterol Education Programme criteria. Coronary artery disease was defined by known myocardial infarction or Q waves on resting electrocardiogram. Results: Metabolically obese nonobese was defined as nonobese subjects (BMI &lt; 25 kg/m2) with MS, MOO as obesity (BMI = 25 kg/m2) with MS, MHO as obese subjects (BMI = 25 kg/m2) with no MS, and MHNO as no obesity or MS. Metabolically obese nonobese was identified in 355 (15.1%), MOO in 348 (14.8%), MHO in 312 (13.3%), and MHNO in 1335 (56.8%) subjects. The prevalence of CAD among the MONO, MOO, MHO, and MHNO was 5.5%, 4.2%, 1.4%, and 2.6%. However, when age standardization was done, there was no statistically significant increase in the risk of CAD among MONO [odds ratio (OR) = 1.300, 95% confidence interval (CI) 0.706–2.394, p = .339], MOO (OR = 1.651, 95% CI 0.852–3.199, p = .137), and MHO (OR = 0.524, 95% CI 0.250–2.130, p = .564) groups compared to MHNO, perhaps due to small numbers. Conclusion: Metabolic obesity may have different clinical implications than phenotypic obesity.</abstract><cop>United States</cop><pub>SAGE Publications</pub><pmid>21527117</pmid><doi>10.1177/193229681100500235</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1932-2968
ispartof Journal of diabetes science and technology, 2011-03, Vol.5 (2), p.439-446
issn 1932-2968
1932-2968
1932-3107
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3125940
source SAGE:Jisc Collections:SAGE Journals Read and Publish 2023-2024:2025 extension (reading list); PubMed Central
subjects Adult
Anthropometry
Blood Glucose - analysis
Body Mass Index
Cholesterol, LDL - metabolism
Coronary Artery Disease - blood
Cross-Sectional Studies
Female
Glucose Tolerance Test
Humans
Hypertension - blood
Hypertriglyceridemia - blood
India
Male
Metabolic Syndrome - blood
Middle Aged
Models, Statistical
Obesity - blood
Obesity - complications
Obesity - epidemiology
Obesity - metabolism
Obesity Technology
Prevalence
title Prevalence and Clinical Profile of Metabolic Obesity and Phenotypic Obesity in Asian Indians
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T22%3A47%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prevalence%20and%20Clinical%20Profile%20of%20Metabolic%20Obesity%20and%20Phenotypic%20Obesity%20in%20Asian%20Indians&rft.jtitle=Journal%20of%20diabetes%20science%20and%20technology&rft.au=Geetha,%20Loganathan&rft.date=2011-03&rft.volume=5&rft.issue=2&rft.spage=439&rft.epage=446&rft.pages=439-446&rft.issn=1932-2968&rft.eissn=1932-2968&rft_id=info:doi/10.1177/193229681100500235&rft_dat=%3Cproquest_pubme%3E864193058%3C/proquest_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c4225-11f4bfa79b09b7769aac121064f591f39d915a5ac1ce7b6801f18b7537b6ec963%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=864193058&rft_id=info:pmid/21527117&rft_sage_id=10.1177_193229681100500235&rfr_iscdi=true