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Associations of metabolic changes and polygenic risk scores with cardiovascular outcomes and all-cause mortality across BMI categories: a prospective cohort study
Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic suscepti...
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| Published in: | Cardiovascular diabetology 2024-07, Vol.23 (1), p.231-17, Article 231 |
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| container_title | Cardiovascular diabetology |
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| creator | Li, Cancan Meng, Xiaoni Zhang, Jie Wang, Haotian Lu, Huimin Cao, Meiling Sun, Shengzhi Wang, Youxin |
| description | Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic susceptibility collectively impact cardiovascular outcomes and all-cause mortality across diverse body mass index (BMI) categories.
In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of |
| doi_str_mv | 10.1186/s12933-024-02332-w |
| format | article |
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In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of < 3 abnormal components (waist circumstance, blood pressure, blood glucose, triglycerides, and high-density lipoprotein cholesterol). Normal weight, overweight, and obesity were defined as 18.5 ≤ BMI < 25 kg/m
, 25 ≤ BMI < 30 kg/m
, and BMI ≥ 30 kg/m
, respectively. Genetic predisposition was estimated using the polygenic risk score (PRS). Cox regressions were performed to evaluate the associations of metabolic status, metabolic transitions, and PRS with cardiovascular outcomes and all-cause mortality across BMI categories.
During a median follow-up of 14.38 years, 31,883 (7.3%) all-cause deaths, 8133 (1.8%) cardiovascular disease (CVD) deaths, and 67,260 (14.8%) CVD cases were documented. Among those with a high PRS, individuals classified as metabolically healthy overweight had the lowest risk of all-cause mortality (hazard ratios [HR] 0.70; 95% confidence interval [CI] 0.65, 0.76) and CVD mortality (HR 0.57; 95% CI 0.50, 0.64) compared to those who were metabolically unhealthy obesity, with the beneficial associations appearing to be greater in the moderate and low PRS groups. Individuals who were metabolically healthy normal weight had the lowest risk of CVD morbidity (HR 0.54; 95% CI 0.51, 0.57). Furthermore, the inverse associations of metabolic status and PRS with cardiovascular outcomes and all-cause mortality across BMI categories were more pronounced among individuals younger than 65 years (P
< 0.05). Additionally, the combined protective effects of metabolic transitions and PRS on these outcomes among BMI categories were observed.
MH status and a low PRS are associated with a lower risk of adverse cardiovascular outcomes and all-cause mortality across all BMI categories. This protective effect is particularly pronounced in individuals younger than 65 years. Further research is required to confirm these findings in diverse populations and to investigate the underlying mechanisms involved.</description><identifier>ISSN: 1475-2840</identifier><identifier>EISSN: 1475-2840</identifier><identifier>DOI: 10.1186/s12933-024-02332-w</identifier><identifier>PMID: 38965592</identifier><language>eng</language><publisher>England: BioMed Central</publisher><subject>Adult ; Aged ; All-cause mortality ; Biobanks ; Blood pressure ; Body Mass Index ; Body weight ; Cardiometabolic Risk Factors ; Cardiovascular disease ; Cardiovascular diseases ; Cardiovascular Diseases - diagnosis ; Cardiovascular Diseases - epidemiology ; Cardiovascular Diseases - genetics ; Cardiovascular Diseases - mortality ; Cause of Death ; Cholesterol ; Education ; Educational attainment ; Exercise ; Family income ; Female ; Genetic diversity ; Genetic Predisposition to Disease ; Genetic Risk Score ; Health risk assessment ; Health risks ; High density lipoprotein ; Humans ; Job requirements ; Male ; Metabolic change ; Metabolic health ; Metabolic syndrome ; Metabolism ; Middle Aged ; Morbidity ; Mortality ; Multifactorial Inheritance ; Obesity ; Obesity - diagnosis ; Obesity - epidemiology ; Obesity - genetics ; Obesity - mortality ; Obesity, Metabolically Benign - diagnosis ; Obesity, Metabolically Benign - epidemiology ; Obesity, Metabolically Benign - genetics ; Obesity, Metabolically Benign - mortality ; Overweight ; Phenotype ; Polygenic risk scores ; Prognosis ; Prospective Studies ; Questionnaires ; Regression analysis ; Risk Assessment ; Risk Factors ; Secondary education ; Socioeconomic factors ; Socioeconomic status ; Stroke ; Time Factors ; Triglycerides ; United Kingdom - epidemiology</subject><ispartof>Cardiovascular diabetology, 2024-07, Vol.23 (1), p.231-17, Article 231</ispartof><rights>2024. The Author(s).</rights><rights>2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c445t-73f1d8627789aefa065b591711b5e738940004d967301febda0ecc70320ce9c73</cites><orcidid>0000-0002-6574-6706</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11225301/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3079227746?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38965592$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Cancan</creatorcontrib><creatorcontrib>Meng, Xiaoni</creatorcontrib><creatorcontrib>Zhang, Jie</creatorcontrib><creatorcontrib>Wang, Haotian</creatorcontrib><creatorcontrib>Lu, Huimin</creatorcontrib><creatorcontrib>Cao, Meiling</creatorcontrib><creatorcontrib>Sun, Shengzhi</creatorcontrib><creatorcontrib>Wang, Youxin</creatorcontrib><title>Associations of metabolic changes and polygenic risk scores with cardiovascular outcomes and all-cause mortality across BMI categories: a prospective cohort study</title><title>Cardiovascular diabetology</title><addtitle>Cardiovasc Diabetol</addtitle><description>Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic susceptibility collectively impact cardiovascular outcomes and all-cause mortality across diverse body mass index (BMI) categories.
In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of < 3 abnormal components (waist circumstance, blood pressure, blood glucose, triglycerides, and high-density lipoprotein cholesterol). Normal weight, overweight, and obesity were defined as 18.5 ≤ BMI < 25 kg/m
, 25 ≤ BMI < 30 kg/m
, and BMI ≥ 30 kg/m
, respectively. Genetic predisposition was estimated using the polygenic risk score (PRS). Cox regressions were performed to evaluate the associations of metabolic status, metabolic transitions, and PRS with cardiovascular outcomes and all-cause mortality across BMI categories.
During a median follow-up of 14.38 years, 31,883 (7.3%) all-cause deaths, 8133 (1.8%) cardiovascular disease (CVD) deaths, and 67,260 (14.8%) CVD cases were documented. Among those with a high PRS, individuals classified as metabolically healthy overweight had the lowest risk of all-cause mortality (hazard ratios [HR] 0.70; 95% confidence interval [CI] 0.65, 0.76) and CVD mortality (HR 0.57; 95% CI 0.50, 0.64) compared to those who were metabolically unhealthy obesity, with the beneficial associations appearing to be greater in the moderate and low PRS groups. Individuals who were metabolically healthy normal weight had the lowest risk of CVD morbidity (HR 0.54; 95% CI 0.51, 0.57). Furthermore, the inverse associations of metabolic status and PRS with cardiovascular outcomes and all-cause mortality across BMI categories were more pronounced among individuals younger than 65 years (P
< 0.05). Additionally, the combined protective effects of metabolic transitions and PRS on these outcomes among BMI categories were observed.
MH status and a low PRS are associated with a lower risk of adverse cardiovascular outcomes and all-cause mortality across all BMI categories. This protective effect is particularly pronounced in individuals younger than 65 years. Further research is required to confirm these findings in diverse populations and to investigate the underlying mechanisms involved.</description><subject>Adult</subject><subject>Aged</subject><subject>All-cause mortality</subject><subject>Biobanks</subject><subject>Blood pressure</subject><subject>Body Mass Index</subject><subject>Body weight</subject><subject>Cardiometabolic Risk Factors</subject><subject>Cardiovascular disease</subject><subject>Cardiovascular diseases</subject><subject>Cardiovascular Diseases - diagnosis</subject><subject>Cardiovascular Diseases - epidemiology</subject><subject>Cardiovascular Diseases - genetics</subject><subject>Cardiovascular Diseases - mortality</subject><subject>Cause of Death</subject><subject>Cholesterol</subject><subject>Education</subject><subject>Educational attainment</subject><subject>Exercise</subject><subject>Family income</subject><subject>Female</subject><subject>Genetic diversity</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic Risk Score</subject><subject>Health risk assessment</subject><subject>Health risks</subject><subject>High density lipoprotein</subject><subject>Humans</subject><subject>Job requirements</subject><subject>Male</subject><subject>Metabolic change</subject><subject>Metabolic health</subject><subject>Metabolic syndrome</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Morbidity</subject><subject>Mortality</subject><subject>Multifactorial Inheritance</subject><subject>Obesity</subject><subject>Obesity - diagnosis</subject><subject>Obesity - epidemiology</subject><subject>Obesity - genetics</subject><subject>Obesity - mortality</subject><subject>Obesity, Metabolically Benign - diagnosis</subject><subject>Obesity, Metabolically Benign - epidemiology</subject><subject>Obesity, Metabolically Benign - genetics</subject><subject>Obesity, Metabolically Benign - mortality</subject><subject>Overweight</subject><subject>Phenotype</subject><subject>Polygenic risk scores</subject><subject>Prognosis</subject><subject>Prospective Studies</subject><subject>Questionnaires</subject><subject>Regression analysis</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>Secondary education</subject><subject>Socioeconomic factors</subject><subject>Socioeconomic status</subject><subject>Stroke</subject><subject>Time Factors</subject><subject>Triglycerides</subject><subject>United Kingdom - epidemiology</subject><issn>1475-2840</issn><issn>1475-2840</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdUk2P0zAQjRCI_YA_wAFZ4sIlMLaTOOaCltUClRZxgbM1cZzWxYmL7bTq3-GX4m3LapeDNdab955mRq8oXlF4R2nbvI-USc5LYFV-nLNy96Q4p5WoS9ZW8PTB_6y4iHENQEXb0OfFGW9lU9eSnRd_rmL02mKyforED2Q0CTvvrCZ6hdPSRIJTTzbe7Zdmymiw8ReJ2ofc2dm0IhpDb_0Wo54dBuLnpP14kqFzpcY5GjL6kNDZtCeog4-RfPq2yNJklj5YEz8QJJuMb4xOdmuI9qssIDHN_f5F8WxAF83LU70sfn6--XH9tbz9_mVxfXVb6qqqUyn4QPu2YUK0Es2A0NRdLamgtKuNyBtXAFD1shEc6GC6HsFoLYAz0EZqwS-LxdG397hWm2BHDHvl0aoD4MNSYUhWO6MGKauuwwYllZVmAgcYaAM9QM37qqbZ6-PRazN3o-m1mVJA98j0cWeyK7X0W0UpY3UeMDu8PTkE_3s2ManRRm2cw8n4OSoOogEGIFmmvvmPuvZzmPKt7liS5ZNUTWaxI-tw_2CG-2koqLs8qWOeVM6TOuRJ7bLo9cM97iX_AsT_AifNyeY</recordid><startdate>20240704</startdate><enddate>20240704</enddate><creator>Li, Cancan</creator><creator>Meng, Xiaoni</creator><creator>Zhang, Jie</creator><creator>Wang, Haotian</creator><creator>Lu, Huimin</creator><creator>Cao, Meiling</creator><creator>Sun, Shengzhi</creator><creator>Wang, Youxin</creator><general>BioMed Central</general><general>BMC</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>7T5</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>H94</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><orcidid>https://orcid.org/0000-0002-6574-6706</orcidid></search><sort><creationdate>20240704</creationdate><title>Associations of metabolic changes and polygenic risk scores with cardiovascular outcomes and all-cause mortality across BMI categories: a prospective cohort study</title><author>Li, Cancan ; Meng, Xiaoni ; Zhang, Jie ; Wang, Haotian ; Lu, Huimin ; Cao, Meiling ; Sun, Shengzhi ; Wang, Youxin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c445t-73f1d8627789aefa065b591711b5e738940004d967301febda0ecc70320ce9c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adult</topic><topic>Aged</topic><topic>All-cause mortality</topic><topic>Biobanks</topic><topic>Blood pressure</topic><topic>Body Mass Index</topic><topic>Body weight</topic><topic>Cardiometabolic Risk Factors</topic><topic>Cardiovascular disease</topic><topic>Cardiovascular diseases</topic><topic>Cardiovascular Diseases - diagnosis</topic><topic>Cardiovascular Diseases - epidemiology</topic><topic>Cardiovascular Diseases - genetics</topic><topic>Cardiovascular Diseases - mortality</topic><topic>Cause of Death</topic><topic>Cholesterol</topic><topic>Education</topic><topic>Educational attainment</topic><topic>Exercise</topic><topic>Family income</topic><topic>Female</topic><topic>Genetic diversity</topic><topic>Genetic Predisposition to Disease</topic><topic>Genetic Risk Score</topic><topic>Health risk assessment</topic><topic>Health risks</topic><topic>High density lipoprotein</topic><topic>Humans</topic><topic>Job requirements</topic><topic>Male</topic><topic>Metabolic change</topic><topic>Metabolic health</topic><topic>Metabolic syndrome</topic><topic>Metabolism</topic><topic>Middle Aged</topic><topic>Morbidity</topic><topic>Mortality</topic><topic>Multifactorial Inheritance</topic><topic>Obesity</topic><topic>Obesity - diagnosis</topic><topic>Obesity - epidemiology</topic><topic>Obesity - genetics</topic><topic>Obesity - mortality</topic><topic>Obesity, Metabolically Benign - diagnosis</topic><topic>Obesity, Metabolically Benign - epidemiology</topic><topic>Obesity, Metabolically Benign - genetics</topic><topic>Obesity, Metabolically Benign - mortality</topic><topic>Overweight</topic><topic>Phenotype</topic><topic>Polygenic risk scores</topic><topic>Prognosis</topic><topic>Prospective Studies</topic><topic>Questionnaires</topic><topic>Regression analysis</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>Secondary education</topic><topic>Socioeconomic factors</topic><topic>Socioeconomic status</topic><topic>Stroke</topic><topic>Time Factors</topic><topic>Triglycerides</topic><topic>United Kingdom - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Cancan</creatorcontrib><creatorcontrib>Meng, Xiaoni</creatorcontrib><creatorcontrib>Zhang, Jie</creatorcontrib><creatorcontrib>Wang, Haotian</creatorcontrib><creatorcontrib>Lu, Huimin</creatorcontrib><creatorcontrib>Cao, Meiling</creatorcontrib><creatorcontrib>Sun, Shengzhi</creatorcontrib><creatorcontrib>Wang, Youxin</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>Immunology Abstracts</collection><collection>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 Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</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>Cardiovascular diabetology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Cancan</au><au>Meng, Xiaoni</au><au>Zhang, Jie</au><au>Wang, Haotian</au><au>Lu, Huimin</au><au>Cao, Meiling</au><au>Sun, Shengzhi</au><au>Wang, Youxin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Associations of metabolic changes and polygenic risk scores with cardiovascular outcomes and all-cause mortality across BMI categories: a prospective cohort study</atitle><jtitle>Cardiovascular diabetology</jtitle><addtitle>Cardiovasc Diabetol</addtitle><date>2024-07-04</date><risdate>2024</risdate><volume>23</volume><issue>1</issue><spage>231</spage><epage>17</epage><pages>231-17</pages><artnum>231</artnum><issn>1475-2840</issn><eissn>1475-2840</eissn><abstract>Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic susceptibility collectively impact cardiovascular outcomes and all-cause mortality across diverse body mass index (BMI) categories.
In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of < 3 abnormal components (waist circumstance, blood pressure, blood glucose, triglycerides, and high-density lipoprotein cholesterol). Normal weight, overweight, and obesity were defined as 18.5 ≤ BMI < 25 kg/m
, 25 ≤ BMI < 30 kg/m
, and BMI ≥ 30 kg/m
, respectively. Genetic predisposition was estimated using the polygenic risk score (PRS). Cox regressions were performed to evaluate the associations of metabolic status, metabolic transitions, and PRS with cardiovascular outcomes and all-cause mortality across BMI categories.
During a median follow-up of 14.38 years, 31,883 (7.3%) all-cause deaths, 8133 (1.8%) cardiovascular disease (CVD) deaths, and 67,260 (14.8%) CVD cases were documented. Among those with a high PRS, individuals classified as metabolically healthy overweight had the lowest risk of all-cause mortality (hazard ratios [HR] 0.70; 95% confidence interval [CI] 0.65, 0.76) and CVD mortality (HR 0.57; 95% CI 0.50, 0.64) compared to those who were metabolically unhealthy obesity, with the beneficial associations appearing to be greater in the moderate and low PRS groups. Individuals who were metabolically healthy normal weight had the lowest risk of CVD morbidity (HR 0.54; 95% CI 0.51, 0.57). Furthermore, the inverse associations of metabolic status and PRS with cardiovascular outcomes and all-cause mortality across BMI categories were more pronounced among individuals younger than 65 years (P
< 0.05). Additionally, the combined protective effects of metabolic transitions and PRS on these outcomes among BMI categories were observed.
MH status and a low PRS are associated with a lower risk of adverse cardiovascular outcomes and all-cause mortality across all BMI categories. This protective effect is particularly pronounced in individuals younger than 65 years. Further research is required to confirm these findings in diverse populations and to investigate the underlying mechanisms involved.</abstract><cop>England</cop><pub>BioMed Central</pub><pmid>38965592</pmid><doi>10.1186/s12933-024-02332-w</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0002-6574-6706</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Cardiovascular diabetology, 2024-07, Vol.23 (1), p.231-17, Article 231 |
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| subjects | Adult Aged All-cause mortality Biobanks Blood pressure Body Mass Index Body weight Cardiometabolic Risk Factors Cardiovascular disease Cardiovascular diseases Cardiovascular Diseases - diagnosis Cardiovascular Diseases - epidemiology Cardiovascular Diseases - genetics Cardiovascular Diseases - mortality Cause of Death Cholesterol Education Educational attainment Exercise Family income Female Genetic diversity Genetic Predisposition to Disease Genetic Risk Score Health risk assessment Health risks High density lipoprotein Humans Job requirements Male Metabolic change Metabolic health Metabolic syndrome Metabolism Middle Aged Morbidity Mortality Multifactorial Inheritance Obesity Obesity - diagnosis Obesity - epidemiology Obesity - genetics Obesity - mortality Obesity, Metabolically Benign - diagnosis Obesity, Metabolically Benign - epidemiology Obesity, Metabolically Benign - genetics Obesity, Metabolically Benign - mortality Overweight Phenotype Polygenic risk scores Prognosis Prospective Studies Questionnaires Regression analysis Risk Assessment Risk Factors Secondary education Socioeconomic factors Socioeconomic status Stroke Time Factors Triglycerides United Kingdom - epidemiology |
| title | Associations of metabolic changes and polygenic risk scores with cardiovascular outcomes and all-cause mortality across BMI categories: a prospective cohort study |
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