5 Breast cancer risk factor analysis
ObjectivesBased on a large-scale epidemiological survey, the study was undertaken to determine the prevalence of breast diseases, to analyze the risk factors and to provide support to the health administration department.MethodsRandom samples were obtained through multi-stage stratified cluster samp...
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| Veröffentlicht in: | Journal of investigative medicine 2019-03, Vol.67 (Suppl 1), p.A2 |
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| creator | Li, CG Meng, FM Zhao, CS |
| description | ObjectivesBased on a large-scale epidemiological survey, the study was undertaken to determine the prevalence of breast diseases, to analyze the risk factors and to provide support to the health administration department.MethodsRandom samples were obtained through multi-stage stratified cluster sampling between 1 March and 1 September 2017. The target population included women aged 18–70 in Jilin Province. All data analyses were performed using SPSS19.0.ResultsThis study found 160 cases of breast cancer, with a mean (SD) age at diagnosis of 53.46 (7.90) years. The high peak of age at diagnosis was between 45 and 65 years. Conditioned multivariate logistic regression analysis identified 4 variables related to breast cancer: history of benign breast tumor, economic status, family history of breast cancer and BMI.ConclusionsThere was an increase in and a trend towards earlier onset in the prevalence of breast cancer in Jilin Province.AcknowledgementsSupported by a project grant from the Bureau of Science and Technology Project (Grand No. 201737167). |
| doi_str_mv | 10.1136/jim-2019-000994.5 |
| format | Article |
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The target population included women aged 18–70 in Jilin Province. All data analyses were performed using SPSS19.0.ResultsThis study found 160 cases of breast cancer, with a mean (SD) age at diagnosis of 53.46 (7.90) years. The high peak of age at diagnosis was between 45 and 65 years. Conditioned multivariate logistic regression analysis identified 4 variables related to breast cancer: history of benign breast tumor, economic status, family history of breast cancer and BMI.ConclusionsThere was an increase in and a trend towards earlier onset in the prevalence of breast cancer in Jilin Province.AcknowledgementsSupported by a project grant from the Bureau of Science and Technology Project (Grand No. 201737167).</description><identifier>ISSN: 1081-5589</identifier><identifier>EISSN: 1708-8267</identifier><identifier>DOI: 10.1136/jim-2019-000994.5</identifier><language>eng</language><publisher>London: Sage Publications Ltd</publisher><subject>Aerobics ; Breast cancer ; Exercise ; Health risk assessment ; Heart failure ; Heart rate ; Neural networks ; Noise ; Physical fitness ; Proteins</subject><ispartof>Journal of investigative medicine, 2019-03, Vol.67 (Suppl 1), p.A2</ispartof><rights>2019, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</rights><rights>2019 2019, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Li, CG</creatorcontrib><creatorcontrib>Meng, FM</creatorcontrib><creatorcontrib>Zhao, CS</creatorcontrib><title>5 Breast cancer risk factor analysis</title><title>Journal of investigative medicine</title><description>ObjectivesBased on a large-scale epidemiological survey, the study was undertaken to determine the prevalence of breast diseases, to analyze the risk factors and to provide support to the health administration department.MethodsRandom samples were obtained through multi-stage stratified cluster sampling between 1 March and 1 September 2017. The target population included women aged 18–70 in Jilin Province. All data analyses were performed using SPSS19.0.ResultsThis study found 160 cases of breast cancer, with a mean (SD) age at diagnosis of 53.46 (7.90) years. The high peak of age at diagnosis was between 45 and 65 years. Conditioned multivariate logistic regression analysis identified 4 variables related to breast cancer: history of benign breast tumor, economic status, family history of breast cancer and BMI.ConclusionsThere was an increase in and a trend towards earlier onset in the prevalence of breast cancer in Jilin Province.AcknowledgementsSupported by a project grant from the Bureau of Science and Technology Project (Grand No. 201737167).</description><subject>Aerobics</subject><subject>Breast cancer</subject><subject>Exercise</subject><subject>Health risk assessment</subject><subject>Heart failure</subject><subject>Heart rate</subject><subject>Neural networks</subject><subject>Noise</subject><subject>Physical fitness</subject><subject>Proteins</subject><issn>1081-5589</issn><issn>1708-8267</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNotkD9PwzAUxC0EEqXwAdgiITHh8p6fndgjVOWPVImlu-UktpTQNMVOh24sfFE-CanCdKfT6XT6MXaLsECk_LFtOi4ADQcAY-RCnbEZFqC5FnlxPnrQyJXS5pJdpdQCiFwZMWP36vf75zl6l4ascrvKxyw26TMLrhr6mLmd2x5Tk67ZRXDb5G_-dc42L6vN8o2vP17fl09rXuaKeKhKQaZUEkOQBZFDoYIQimpVO0H1GGow2ptcesJCglSBRNDSlxXVGmjO7qbZfey_Dj4Ntu0PcfyQrEBdoATQNLYeplbZtXYfm87Fo0WwJxB2BGFPIOwEwir6A1Y-TzE</recordid><startdate>201903</startdate><enddate>201903</enddate><creator>Li, CG</creator><creator>Meng, FM</creator><creator>Zhao, CS</creator><general>Sage Publications Ltd</general><scope>0-V</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AM</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGRYB</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K7.</scope><scope>K9.</scope><scope>M0O</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>201903</creationdate><title>5 Breast cancer risk factor analysis</title><author>Li, CG ; Meng, FM ; Zhao, CS</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b653-fcb239b541ff4733a125f2253d5da23df478098e964e3174045f32f84ebc3d803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Aerobics</topic><topic>Breast cancer</topic><topic>Exercise</topic><topic>Health risk assessment</topic><topic>Heart failure</topic><topic>Heart rate</topic><topic>Neural networks</topic><topic>Noise</topic><topic>Physical fitness</topic><topic>Proteins</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, CG</creatorcontrib><creatorcontrib>Meng, FM</creatorcontrib><creatorcontrib>Zhao, CS</creatorcontrib><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Criminal Justice 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>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Criminology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Criminal Justice (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Criminal Justice Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</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 Basic</collection><jtitle>Journal of investigative medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, CG</au><au>Meng, FM</au><au>Zhao, CS</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>5 Breast cancer risk factor analysis</atitle><jtitle>Journal of investigative medicine</jtitle><date>2019-03</date><risdate>2019</risdate><volume>67</volume><issue>Suppl 1</issue><spage>A2</spage><pages>A2-</pages><issn>1081-5589</issn><eissn>1708-8267</eissn><abstract>ObjectivesBased on a large-scale epidemiological survey, the study was undertaken to determine the prevalence of breast diseases, to analyze the risk factors and to provide support to the health administration department.MethodsRandom samples were obtained through multi-stage stratified cluster sampling between 1 March and 1 September 2017. The target population included women aged 18–70 in Jilin Province. All data analyses were performed using SPSS19.0.ResultsThis study found 160 cases of breast cancer, with a mean (SD) age at diagnosis of 53.46 (7.90) years. The high peak of age at diagnosis was between 45 and 65 years. Conditioned multivariate logistic regression analysis identified 4 variables related to breast cancer: history of benign breast tumor, economic status, family history of breast cancer and BMI.ConclusionsThere was an increase in and a trend towards earlier onset in the prevalence of breast cancer in Jilin Province.AcknowledgementsSupported by a project grant from the Bureau of Science and Technology Project (Grand No. 201737167).</abstract><cop>London</cop><pub>Sage Publications Ltd</pub><doi>10.1136/jim-2019-000994.5</doi></addata></record> |
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| subjects | Aerobics Breast cancer Exercise Health risk assessment Heart failure Heart rate Neural networks Noise Physical fitness Proteins |
| title | 5 Breast cancer risk factor analysis |
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