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Prevalence and Influencing Factors of Metabolic Syndrome among Adults in China from 2015 to 2017
The prevalence and influencing factors of metabolic syndrome (MetS) in Chinese residents aged 20 or older were investigated. The data were collected from China Nutrition and Health Surveillance (2015-2017), which used a stratified, multistage, random sampling method. A total of 130,018 residents age...
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Published in: | Nutrients 2021-12, Vol.13 (12), p.4475 |
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description | The prevalence and influencing factors of metabolic syndrome (MetS) in Chinese residents aged 20 or older were investigated. The data were collected from China Nutrition and Health Surveillance (2015-2017), which used a stratified, multistage, random sampling method. A total of 130,018 residents aged 20 years or older from 31 provinces were included in this study. The National Cholesterol Education Programme Adult Treatment Panel III (NCEP ATP III) criteria were used to define MetS. The standardised prevalence of high waist circumference, high blood pressure and low high-density lipoprotein cholesterol were 40.8%, 49.4% and 41.1%, respectively. The following factors were associated with a higher prevalence of MetS: female [odds ratio (OR) = 1.773, 95% CI = 1.709-1.840]; older age (OR = 1.037, 95% CI = 1.036-1.039); living in north China (OR = 1.087, 95% CI = 1.058-1.117); high body mass index (OR = 1.402, 95% CI = 1.395-1.408); higher income [OR (95% CI): 1.044 (1.007-1.083), 1.083 (1.044-1.124) and 1.123 (1.078-1.170) for moderate, high, and very high income, respectively]; family history of hypertension (OR = 1.237, 95% CI = 1.203-1.273); family history of diabetes (OR = 1.491, 95% CI = 1.426-1.558) and current smoking status (OR = 1.143, 95% CI = 1.098-1.191). Living in the countryside (OR = 0.960, 95% CI = 0.932-0.988), moderate alcohol consumption (OR = 0.917, 95% CI = 0.889-0.946) and being physically active (OR = 0.887, 95% CI = 0.862-0.913) were associated with a lower prevalence of MetS. The prevalence of MetS among residents aged 20 years or older in China is increasing, especially among women, people aged 45 years or older and urban residents. Preventive efforts, such as quitting smoking and engaging in physical activity, are recommended to reduce the risk of MetS. |
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The data were collected from China Nutrition and Health Surveillance (2015-2017), which used a stratified, multistage, random sampling method. A total of 130,018 residents aged 20 years or older from 31 provinces were included in this study. The National Cholesterol Education Programme Adult Treatment Panel III (NCEP ATP III) criteria were used to define MetS. The standardised prevalence of high waist circumference, high blood pressure and low high-density lipoprotein cholesterol were 40.8%, 49.4% and 41.1%, respectively. The following factors were associated with a higher prevalence of MetS: female [odds ratio (OR) = 1.773, 95% CI = 1.709-1.840]; older age (OR = 1.037, 95% CI = 1.036-1.039); living in north China (OR = 1.087, 95% CI = 1.058-1.117); high body mass index (OR = 1.402, 95% CI = 1.395-1.408); higher income [OR (95% CI): 1.044 (1.007-1.083), 1.083 (1.044-1.124) and 1.123 (1.078-1.170) for moderate, high, and very high income, respectively]; family history of hypertension (OR = 1.237, 95% CI = 1.203-1.273); family history of diabetes (OR = 1.491, 95% CI = 1.426-1.558) and current smoking status (OR = 1.143, 95% CI = 1.098-1.191). Living in the countryside (OR = 0.960, 95% CI = 0.932-0.988), moderate alcohol consumption (OR = 0.917, 95% CI = 0.889-0.946) and being physically active (OR = 0.887, 95% CI = 0.862-0.913) were associated with a lower prevalence of MetS. The prevalence of MetS among residents aged 20 years or older in China is increasing, especially among women, people aged 45 years or older and urban residents. Preventive efforts, such as quitting smoking and engaging in physical activity, are recommended to reduce the risk of MetS.</description><identifier>ISSN: 2072-6643</identifier><identifier>EISSN: 2072-6643</identifier><identifier>DOI: 10.3390/nu13124475</identifier><identifier>PMID: 34960027</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Adult ; adults ; Alcohol ; Blood pressure ; Body mass ; Body mass index ; Body size ; China - epidemiology ; Cholesterol ; Diabetes ; Diabetes mellitus ; Education ; Fasting ; Female ; Fruits ; Genetics ; Health surveillance ; High density lipoprotein ; Humans ; Hypertension ; influencing factors ; Laboratories ; Logistic Models ; Male ; Meat ; Metabolic disorders ; Metabolic syndrome ; Metabolic Syndrome - epidemiology ; Metabolic Syndrome - etiology ; Middle Aged ; Multivariate Analysis ; Nutrition ; Physical activity ; Population Surveillance ; Prevalence ; Quality control ; Questionnaires ; Random sampling ; Retrospective Studies ; Risk Factors ; Risk reduction ; Rural areas ; Smoking ; Statistical sampling ; Surveys and Questionnaires ; Young Adult</subject><ispartof>Nutrients, 2021-12, Vol.13 (12), p.4475</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c538t-c7b873b8e2f58c87696753434b316f76888d8f2cd904a18a5ef6c587f0dd38a53</citedby><cites>FETCH-LOGICAL-c538t-c7b873b8e2f58c87696753434b316f76888d8f2cd904a18a5ef6c587f0dd38a53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2612820785/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2612820785?pq-origsite=primo$$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/34960027$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yao, Fan</creatorcontrib><creatorcontrib>Bo, Yacong</creatorcontrib><creatorcontrib>Zhao, Liyun</creatorcontrib><creatorcontrib>Li, Yaru</creatorcontrib><creatorcontrib>Ju, Lahong</creatorcontrib><creatorcontrib>Fang, Hongyun</creatorcontrib><creatorcontrib>Piao, Wei</creatorcontrib><creatorcontrib>Yu, Dongmei</creatorcontrib><creatorcontrib>Lao, Xiangqian</creatorcontrib><title>Prevalence and Influencing Factors of Metabolic Syndrome among Adults in China from 2015 to 2017</title><title>Nutrients</title><addtitle>Nutrients</addtitle><description>The prevalence and influencing factors of metabolic syndrome (MetS) in Chinese residents aged 20 or older were investigated. The data were collected from China Nutrition and Health Surveillance (2015-2017), which used a stratified, multistage, random sampling method. A total of 130,018 residents aged 20 years or older from 31 provinces were included in this study. The National Cholesterol Education Programme Adult Treatment Panel III (NCEP ATP III) criteria were used to define MetS. The standardised prevalence of high waist circumference, high blood pressure and low high-density lipoprotein cholesterol were 40.8%, 49.4% and 41.1%, respectively. The following factors were associated with a higher prevalence of MetS: female [odds ratio (OR) = 1.773, 95% CI = 1.709-1.840]; older age (OR = 1.037, 95% CI = 1.036-1.039); living in north China (OR = 1.087, 95% CI = 1.058-1.117); high body mass index (OR = 1.402, 95% CI = 1.395-1.408); higher income [OR (95% CI): 1.044 (1.007-1.083), 1.083 (1.044-1.124) and 1.123 (1.078-1.170) for moderate, high, and very high income, respectively]; family history of hypertension (OR = 1.237, 95% CI = 1.203-1.273); family history of diabetes (OR = 1.491, 95% CI = 1.426-1.558) and current smoking status (OR = 1.143, 95% CI = 1.098-1.191). Living in the countryside (OR = 0.960, 95% CI = 0.932-0.988), moderate alcohol consumption (OR = 0.917, 95% CI = 0.889-0.946) and being physically active (OR = 0.887, 95% CI = 0.862-0.913) were associated with a lower prevalence of MetS. The prevalence of MetS among residents aged 20 years or older in China is increasing, especially among women, people aged 45 years or older and urban residents. Preventive efforts, such as quitting smoking and engaging in physical activity, are recommended to reduce the risk of MetS.</description><subject>Adult</subject><subject>adults</subject><subject>Alcohol</subject><subject>Blood pressure</subject><subject>Body mass</subject><subject>Body mass index</subject><subject>Body size</subject><subject>China - epidemiology</subject><subject>Cholesterol</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Education</subject><subject>Fasting</subject><subject>Female</subject><subject>Fruits</subject><subject>Genetics</subject><subject>Health surveillance</subject><subject>High density lipoprotein</subject><subject>Humans</subject><subject>Hypertension</subject><subject>influencing factors</subject><subject>Laboratories</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Meat</subject><subject>Metabolic disorders</subject><subject>Metabolic syndrome</subject><subject>Metabolic Syndrome - epidemiology</subject><subject>Metabolic Syndrome - etiology</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>Nutrition</subject><subject>Physical activity</subject><subject>Population Surveillance</subject><subject>Prevalence</subject><subject>Quality control</subject><subject>Questionnaires</subject><subject>Random sampling</subject><subject>Retrospective Studies</subject><subject>Risk Factors</subject><subject>Risk reduction</subject><subject>Rural areas</subject><subject>Smoking</subject><subject>Statistical sampling</subject><subject>Surveys and Questionnaires</subject><subject>Young Adult</subject><issn>2072-6643</issn><issn>2072-6643</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkltrFTEQxxex2FL74geQgC8iHM092RehHFo90KKgPsdsLqc5ZJOa7Bb67c321F7My2RmfvwzmZmue4PgR0J6-CnNiCBMqWAvuiMMBV5xTsnLJ_fD7qTWHVyOgIKTV90hoT2HEIuj7vf34m50dMk4oJMFm-Tj3LyQtuBcmymXCrIHl27SQ47BgB-3yZY8NnrMjTm1c5wqCAmsr0LSwLccwBAxMOXFitfdgdexupN7e9z9Oj_7uf66uvj2ZbM-vVgZRuS0MmKQggzSYc-kkYL3XDBCCR0I4l5wKaWVHhvbQ6qR1Mx5bpgUHlpLmkuOu81e12a9U9cljLrcqqyDugvkslW6TMFEpwjvewIhQoYISjGS7VWL-8EJ00tMRdP6vNe6nofRWePSVHR8Jvo8k8KV2uYbJQVknPZN4P29QMl_ZlcnNYZqXIw6uTxXhTliCGEJZUPf_Yfu8lxSa9VCYdnGKJfffdhTpuRai_MPxSColj1Qj3vQ4LdPy39A_02d_AUmG6m2</recordid><startdate>20211215</startdate><enddate>20211215</enddate><creator>Yao, Fan</creator><creator>Bo, Yacong</creator><creator>Zhao, Liyun</creator><creator>Li, Yaru</creator><creator>Ju, Lahong</creator><creator>Fang, Hongyun</creator><creator>Piao, Wei</creator><creator>Yu, Dongmei</creator><creator>Lao, Xiangqian</creator><general>MDPI AG</general><general>MDPI</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>3V.</scope><scope>7TS</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20211215</creationdate><title>Prevalence and Influencing Factors of Metabolic Syndrome among Adults in China from 2015 to 2017</title><author>Yao, Fan ; Bo, Yacong ; Zhao, Liyun ; Li, Yaru ; Ju, Lahong ; Fang, Hongyun ; Piao, Wei ; Yu, Dongmei ; Lao, Xiangqian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c538t-c7b873b8e2f58c87696753434b316f76888d8f2cd904a18a5ef6c587f0dd38a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adult</topic><topic>adults</topic><topic>Alcohol</topic><topic>Blood pressure</topic><topic>Body mass</topic><topic>Body mass index</topic><topic>Body size</topic><topic>China - epidemiology</topic><topic>Cholesterol</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Education</topic><topic>Fasting</topic><topic>Female</topic><topic>Fruits</topic><topic>Genetics</topic><topic>Health surveillance</topic><topic>High density lipoprotein</topic><topic>Humans</topic><topic>Hypertension</topic><topic>influencing factors</topic><topic>Laboratories</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Meat</topic><topic>Metabolic disorders</topic><topic>Metabolic syndrome</topic><topic>Metabolic Syndrome - epidemiology</topic><topic>Metabolic Syndrome - etiology</topic><topic>Middle Aged</topic><topic>Multivariate Analysis</topic><topic>Nutrition</topic><topic>Physical activity</topic><topic>Population Surveillance</topic><topic>Prevalence</topic><topic>Quality control</topic><topic>Questionnaires</topic><topic>Random sampling</topic><topic>Retrospective Studies</topic><topic>Risk Factors</topic><topic>Risk reduction</topic><topic>Rural areas</topic><topic>Smoking</topic><topic>Statistical sampling</topic><topic>Surveys and Questionnaires</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yao, Fan</creatorcontrib><creatorcontrib>Bo, Yacong</creatorcontrib><creatorcontrib>Zhao, Liyun</creatorcontrib><creatorcontrib>Li, Yaru</creatorcontrib><creatorcontrib>Ju, Lahong</creatorcontrib><creatorcontrib>Fang, Hongyun</creatorcontrib><creatorcontrib>Piao, Wei</creatorcontrib><creatorcontrib>Yu, Dongmei</creatorcontrib><creatorcontrib>Lao, Xiangqian</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Physical Education Index</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Nutrients</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yao, Fan</au><au>Bo, Yacong</au><au>Zhao, Liyun</au><au>Li, Yaru</au><au>Ju, Lahong</au><au>Fang, Hongyun</au><au>Piao, Wei</au><au>Yu, Dongmei</au><au>Lao, Xiangqian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prevalence and Influencing Factors of Metabolic Syndrome among Adults in China from 2015 to 2017</atitle><jtitle>Nutrients</jtitle><addtitle>Nutrients</addtitle><date>2021-12-15</date><risdate>2021</risdate><volume>13</volume><issue>12</issue><spage>4475</spage><pages>4475-</pages><issn>2072-6643</issn><eissn>2072-6643</eissn><abstract>The prevalence and influencing factors of metabolic syndrome (MetS) in Chinese residents aged 20 or older were investigated. The data were collected from China Nutrition and Health Surveillance (2015-2017), which used a stratified, multistage, random sampling method. A total of 130,018 residents aged 20 years or older from 31 provinces were included in this study. The National Cholesterol Education Programme Adult Treatment Panel III (NCEP ATP III) criteria were used to define MetS. The standardised prevalence of high waist circumference, high blood pressure and low high-density lipoprotein cholesterol were 40.8%, 49.4% and 41.1%, respectively. The following factors were associated with a higher prevalence of MetS: female [odds ratio (OR) = 1.773, 95% CI = 1.709-1.840]; older age (OR = 1.037, 95% CI = 1.036-1.039); living in north China (OR = 1.087, 95% CI = 1.058-1.117); high body mass index (OR = 1.402, 95% CI = 1.395-1.408); higher income [OR (95% CI): 1.044 (1.007-1.083), 1.083 (1.044-1.124) and 1.123 (1.078-1.170) for moderate, high, and very high income, respectively]; family history of hypertension (OR = 1.237, 95% CI = 1.203-1.273); family history of diabetes (OR = 1.491, 95% CI = 1.426-1.558) and current smoking status (OR = 1.143, 95% CI = 1.098-1.191). Living in the countryside (OR = 0.960, 95% CI = 0.932-0.988), moderate alcohol consumption (OR = 0.917, 95% CI = 0.889-0.946) and being physically active (OR = 0.887, 95% CI = 0.862-0.913) were associated with a lower prevalence of MetS. The prevalence of MetS among residents aged 20 years or older in China is increasing, especially among women, people aged 45 years or older and urban residents. Preventive efforts, such as quitting smoking and engaging in physical activity, are recommended to reduce the risk of MetS.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>34960027</pmid><doi>10.3390/nu13124475</doi><oa>free_for_read</oa></addata></record> |
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subjects | Adult adults Alcohol Blood pressure Body mass Body mass index Body size China - epidemiology Cholesterol Diabetes Diabetes mellitus Education Fasting Female Fruits Genetics Health surveillance High density lipoprotein Humans Hypertension influencing factors Laboratories Logistic Models Male Meat Metabolic disorders Metabolic syndrome Metabolic Syndrome - epidemiology Metabolic Syndrome - etiology Middle Aged Multivariate Analysis Nutrition Physical activity Population Surveillance Prevalence Quality control Questionnaires Random sampling Retrospective Studies Risk Factors Risk reduction Rural areas Smoking Statistical sampling Surveys and Questionnaires Young Adult |
title | Prevalence and Influencing Factors of Metabolic Syndrome among Adults in China from 2015 to 2017 |
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