The Age-Specific Quantitative Effects of Metabolic Risk Factors on Cardiovascular Diseases and Diabetes: A Pooled Analysis
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J.", "last_name"=>"Brunner", "scopus_author_id"=>"24576354300"}, {"first_name"=>"M.", "last_name"=>"Shipley", "scopus_author_id"=>"7103265845"}, {"first_name"=>"J.", "last_name"=>"Buring", "scopus_author_id"=>"56750904300"}, {"first_name"=>"J.", "last_name"=>"Shepherd", "scopus_author_id"=>"7401741461"}, {"first_name"=>"S. M.", "last_name"=>"Cobbe", "scopus_author_id"=>"35227092200"}, {"first_name"=>"I.", "last_name"=>"Ford", "scopus_author_id"=>"7006691891"}, {"first_name"=>"J. W.", "last_name"=>"Jukema", "scopus_author_id"=>"7005836769"}, {"first_name"=>"A.", "last_name"=>"Marín Ibañez", "scopus_author_id"=>"6506800828"}, {"first_name"=>"E. J.M.", "last_name"=>"Feskens", "scopus_author_id"=>"7005435520"}, {"first_name"=>"D.", "last_name"=>"Kromhout", "scopus_author_id"=>"40261987600"}, {"first_name"=>"M.", "last_name"=>"Alexander", "scopus_author_id"=>"35809815600"}, {"first_name"=>"A.", "last_name"=>"Butterworth", "scopus_author_id"=>"57201120111"}, {"first_name"=>"E.", "last_name"=>"Di Angelantonio", "scopus_author_id"=>"57191477098"}, {"first_name"=>"P.", "last_name"=>"Gao", "scopus_author_id"=>"35069449800"}, {"first_name"=>"S.", "last_name"=>"Kaptoge", "scopus_author_id"=>"35781340500"}, {"first_name"=>"S.", "last_name"=>"Lewington", "scopus_author_id"=>"57193198060"}, {"first_name"=>"L.", "last_name"=>"Pennells", "scopus_author_id"=>"28367864900"}, {"first_name"=>"S. G.", "last_name"=>"Thompson", "scopus_author_id"=>"7403232897"}, {"first_name"=>"M.", "last_name"=>"Walker", "scopus_author_id"=>"14523962000"}, {"first_name"=>"S.", "last_name"=>"Watson", "scopus_author_id"=>"55500430200"}, {"first_name"=>"I. R.", "last_name"=>"White", "scopus_author_id"=>"35235524000"}, {"first_name"=>"A. M.", "last_name"=>"Wood", "scopus_author_id"=>"10040876400"}, {"first_name"=>"D.", "last_name"=>"Wormser", "scopus_author_id"=>"57193196178"}, {"first_name"=>"J.", "last_name"=>"Danesh", "scopus_author_id"=>"7006642150"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"369443231", "sgr"=>"84880795072", "issn"=>"19326203", "arxiv"=>"arXiv:1011.1669v3", "pmid"=>"23935815", "scopus"=>"2-s2.0-84880795072", "doi"=>"10.1371/journal.pone.0065174", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)"}, "id"=>"cd05b531-8209-3b6a-9dc2-83fddc31a430", "abstract"=>"BACKGROUND: The effects of systolic blood pressure (SBP), serum total cholesterol (TC), fasting plasma glucose (FPG), and body mass index (BMI) on the risk of cardiovascular diseases (CVD) have been established in epidemiological studies, but consistent estimates of effect sizes by age and sex are not available.\\n\\nMETHODS: We reviewed large cohort pooling projects, evaluating effects of baseline or usual exposure to metabolic risks on ischemic heart disease (IHD), hypertensive heart disease (HHD), stroke, diabetes, and, as relevant selected other CVDs, after adjusting for important confounders. We pooled all data to estimate relative risks (RRs) for each risk factor and examined effect modification by age or other factors, using random effects models.\\n\\nRESULTS: Across all risk factors, an average of 123 cohorts provided data on 1.4 million individuals and 52,000 CVD events. Each metabolic risk factor was robustly related to CVD. At the baseline age of 55-64 years, the RR for 10 mmHg higher SBP was largest for HHD (2.16; 95% CI 2.09-2.24), followed by effects on both stroke subtypes (1.66; 1.39-1.98 for hemorrhagic stroke and 1.63; 1.57-1.69 for ischemic stroke). In the same age group, RRs for 1 mmol/L higher TC were 1.44 (1.29-1.61) for IHD and 1.20 (1.15-1.25) for ischemic stroke. The RRs for 5 kg/m(2) higher BMI for ages 55-64 ranged from 2.32 (2.04-2.63) for diabetes, to 1.44 (1.40-1.48) for IHD. For 1 mmol/L higher FPG, RRs in this age group were 1.18 (1.08-1.29) for IHD and 1.14 (1.01-1.29) for total stroke. For all risk factors, proportional effects declined with age, were generally consistent by sex, and differed by region in only a few age groups for certain risk factor-disease pairs.\\n\\nCONCLUSION: Our results provide robust, comparable and precise estimates of the effects of major metabolic risk factors on CVD and diabetes by age group.", "link"=>"http://www.mendeley.com/research/agespecific-quantitative-effects-metabolic-risk-factors-cardiovascular-diseases-diabetes-pooled-anal-5", "reader_count"=>147, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>6, "Researcher"=>29, "Student > Doctoral Student"=>13, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>9, "Student > Master"=>29, "Other"=>6, "Student > Bachelor"=>19, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>3, "Professor"=>8}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>6, "Researcher"=>29, "Student > Doctoral Student"=>13, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>9, "Student > Master"=>29, "Other"=>6, "Student > Bachelor"=>19, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>3, "Professor"=>8}, "reader_count_by_subject_area"=>{"Unspecified"=>8, "Agricultural and Biological Sciences"=>14, "Arts and Humanities"=>2, "Business, Management and Accounting"=>1, "Chemistry"=>3, "Computer Science"=>2, "Decision Sciences"=>1, "Earth and Planetary Sciences"=>2, "Economics, Econometrics and Finance"=>1, "Engineering"=>1, "Environmental Science"=>4, "Nursing and Health Professions"=>10, "Biochemistry, Genetics and Molecular Biology"=>9, "Materials Science"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>68, "Neuroscience"=>2, "Pharmacology, Toxicology and Pharmaceutical Science"=>9, "Sports and Recreations"=>2, "Physics and Astronomy"=>2, "Psychology"=>1, "Social Sciences"=>3}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>68}, "Social Sciences"=>{"Social Sciences"=>3}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Psychology"=>{"Psychology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>8}, "Environmental Science"=>{"Environmental Science"=>4}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>9}, "Arts and Humanities"=>{"Arts and Humanities"=>2}, "Engineering"=>{"Engineering"=>1}, "Chemistry"=>{"Chemistry"=>3}, "Neuroscience"=>{"Neuroscience"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>2}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>14}, "Computer Science"=>{"Computer Science"=>2}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>10}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>9}}, "reader_count_by_country"=>{"United Kingdom"=>2, "Malaysia"=>1, "India"=>1}, "group_count"=>8}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1137107"], "description"=>"<p>The figure shows RRs for 10 mmHg higher usual SBP. The figure shows RRs converted to comparable age group as described in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065174#s2\" target=\"_blank\">Methods</a>. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065174#pone.0065174.s001\" target=\"_blank\">Table S1</a> for RRs in original age groups from each study. RRs for rheumatic heart disease and inflammatory heart disease apply only to deaths and those for other outcomes to deaths and incidence. The percentage of variation in the pooled estimates that is due to statistical heterogeneity was evaluated using the I<sup>2</sup> statistic for each age group and outcome. Of all outcomes and age groups analyzed, only two age groups in the pooled analysis for hemorrhagic stroke had non-zero I<sup>2</sup> values: I<sup>2</sup> = 44.4% for ages 35–44 years, and I<sup>2</sup> = 24.3% for ages 55–64 years.</p>", "links"=>[], "tags"=>["cardiovascular", "Coronary artery disease", "hypertension", "stroke", "Clinical research design", "Cohort studies", "Endocrinology", "Diabetic endocrinology", "epidemiology", "Cardiovascular disease epidemiology", "Epidemiological methods", "Global health", "Metabolic disorders", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Public health", "preventive medicine", "risks", "diseases", "systolic"], "article_id"=>759843, "categories"=>["Medicine"], "users"=>["Gitanjali M. Singh", "Goodarz Danaei", "Farshad Farzadfar", "Gretchen A. Stevens", "Mark Woodward", "David Wormser", "Stephen Kaptoge", "Gary Whitlock", "Qing Qiao", "Sarah Lewington", "Emanuele Di Angelantonio", "Stephen Vander Hoorn", "Carlene M. M. Lawes", "Mohammed K. Ali", "Dariush Mozaffarian", "Majid Ezzati"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0065174.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Relative_risks_RRs_for_diseases_associated_with_systolic_blood_pressure_SBP_/759843", "title"=>"Relative risks (RRs) for diseases associated with systolic blood pressure (SBP).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-30 08:19:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1137108"], "description"=>"<p>The figure shows RRs for 1 mmol/L higher usual TC. The figure shows RRs converted to comparable age group as described in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065174#s2\" target=\"_blank\">Methods</a>. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065174#pone.0065174.s001\" target=\"_blank\">Table S1</a> for RRs in original age groups from each study. The percentage of variation in the pooled estimates that is due to statistical heterogeneity was evaluated using the I<sup>2</sup> statistic for each age group and outcome. Of all the outcomes and age groups analyzed, only ages 35–44 years in the pooled analysis for IHD had a non-zero I<sup>2</sup> value of 58.8%.</p>", "links"=>[], "tags"=>["cardiovascular", "Coronary artery disease", "hypertension", "stroke", "Clinical research design", "Cohort studies", "Endocrinology", "Diabetic endocrinology", "epidemiology", "Cardiovascular disease epidemiology", "Epidemiological methods", "Global health", "Metabolic disorders", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Public health", "preventive medicine", "risks", "diseases", "serum"], "article_id"=>759844, "categories"=>["Medicine"], "users"=>["Gitanjali M. Singh", "Goodarz Danaei", "Farshad Farzadfar", "Gretchen A. Stevens", "Mark Woodward", "David Wormser", "Stephen Kaptoge", "Gary Whitlock", "Qing Qiao", "Sarah Lewington", "Emanuele Di Angelantonio", "Stephen Vander Hoorn", "Carlene M. M. Lawes", "Mohammed K. Ali", "Dariush Mozaffarian", "Majid Ezzati"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0065174.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Relative_risks_RRs_for_diseases_associated_with_serum_total_cholesterol_TC_/759844", "title"=>"Relative risks (RRs) for diseases associated with serum total cholesterol (TC).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-30 08:19:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1137109"], "description"=>"<p>The figure shows RRs for 5 kg/m<sup>2</sup> higher baseline BMI. The figure shows RRs converted to comparable age group as described in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065174#s2\" target=\"_blank\">Methods</a>. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065174#pone.0065174.s001\" target=\"_blank\">Table S1</a> for RRs in original age groups from each study. The percentage of variation in the pooled estimates that is due to statistical heterogeneity was evaluated using the I<sup>2</sup> statistic for each age group and outcome. Of all the outcomes and age groups analyzed, the three age groups below age 65 years in the pooled analysis for hypertensive heart disease had non-zero I<sup>2</sup> values: 79.2% for ages 35–44 years, 69.0% for ages 45–54 years, and 37.2% for ages 55–64 years. *The associations with haemorrhagic stroke are for BMIs above 25 kg/m<sup>2</sup> as described in text.</p>", "links"=>[], "tags"=>["cardiovascular", "Coronary artery disease", "hypertension", "stroke", "Clinical research design", "Cohort studies", "Endocrinology", "Diabetic endocrinology", "epidemiology", "Cardiovascular disease epidemiology", "Epidemiological methods", "Global health", "Metabolic disorders", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Public health", "preventive medicine", "risks", "diseases"], "article_id"=>759845, "categories"=>["Medicine"], "users"=>["Gitanjali M. Singh", "Goodarz Danaei", "Farshad Farzadfar", "Gretchen A. Stevens", "Mark Woodward", "David Wormser", "Stephen Kaptoge", "Gary Whitlock", "Qing Qiao", "Sarah Lewington", "Emanuele Di Angelantonio", "Stephen Vander Hoorn", "Carlene M. M. Lawes", "Mohammed K. Ali", "Dariush Mozaffarian", "Majid Ezzati"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0065174.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Relative_risks_RRs_for_diseases_associated_with_body_mass_index_BMI_/759845", "title"=>"Relative risks (RRs) for diseases associated with body mass index (BMI).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-30 08:19:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1137110"], "description"=>"<p>The figure shows RRs for 1 mmol/L higher usual or baseline FPG. The figure shows RRs converted to comparable age group as described in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065174#s2\" target=\"_blank\">Methods</a>. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065174#pone.0065174.s001\" target=\"_blank\">Table S1</a> for RRs in original age groups from each study. The percentage of variation in the pooled estimates that is due to statistical heterogeneity was evaluated using the I<sup>2</sup> statistic for each age group and outcome. All I<sup>2</sup> values for these outcomes and age groups were zero.</p>", "links"=>[], "tags"=>["cardiovascular", "Coronary artery disease", "hypertension", "stroke", "Clinical research design", "Cohort studies", "Endocrinology", "Diabetic endocrinology", "epidemiology", "Cardiovascular disease epidemiology", "Epidemiological methods", "Global health", "Metabolic disorders", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Public health", "preventive medicine", "risks", "diseases", "fasting", "plasma", "glucose"], "article_id"=>759846, "categories"=>["Medicine"], "users"=>["Gitanjali M. Singh", "Goodarz Danaei", "Farshad Farzadfar", "Gretchen A. Stevens", "Mark Woodward", "David Wormser", "Stephen Kaptoge", "Gary Whitlock", "Qing Qiao", "Sarah Lewington", "Emanuele Di Angelantonio", "Stephen Vander Hoorn", "Carlene M. M. Lawes", "Mohammed K. Ali", "Dariush Mozaffarian", "Majid Ezzati"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0065174.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Relative_risks_RRs_for_diseases_associated_with_fasting_plasma_glucose_FPG_/759846", "title"=>"Relative risks (RRs) for diseases associated with fasting plasma glucose (FPG).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-30 08:19:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1137111"], "description"=>"a<p>RRs apply to mortality but not to incidence and is included because of the benefits of lower blood pressure for reduced heart failure mortality.</p>b<p>This residual category contains a number of ICD codes. The proportion of deaths from the constituent diseases is likely to vary across world regions and even across cohorts in the same meta-analysis.</p>c<p>A quadratic age model was used instead of a log-linear age model as this fit the data better.</p>", "links"=>[], "tags"=>["cardiovascular", "Coronary artery disease", "hypertension", "stroke", "Clinical research design", "Cohort studies", "Endocrinology", "Diabetic endocrinology", "epidemiology", "Cardiovascular disease epidemiology", "Epidemiological methods", "Global health", "Metabolic disorders", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Public health", "preventive medicine", "studies", "rrs", "procedures", "estimating"], "article_id"=>759847, "categories"=>["Medicine"], "users"=>["Gitanjali M. Singh", "Goodarz Danaei", "Farshad Farzadfar", "Gretchen A. Stevens", "Mark Woodward", "David Wormser", "Stephen Kaptoge", "Gary Whitlock", "Qing Qiao", "Sarah Lewington", "Emanuele Di Angelantonio", "Stephen Vander Hoorn", "Carlene M. M. Lawes", "Mohammed K. Ali", "Dariush Mozaffarian", "Majid Ezzati"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0065174.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Outcomes_associated_with_each_risk_factor_studies_from_which_RRs_were_extracted_and_procedures_for_estimating_RRs_by_age_group_/759847", "title"=>"Outcomes associated with each risk factor, studies from which RRs were extracted, and procedures for estimating RRs by age group.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-30 08:19:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1137112"], "description"=>"<div><p>Background</p><p>The effects of systolic blood pressure (SBP), serum total cholesterol (TC), fasting plasma glucose (FPG), and body mass index (BMI) on the risk of cardiovascular diseases (CVD) have been established in epidemiological studies, but consistent estimates of effect sizes by age and sex are not available.</p><p>Methods</p><p>We reviewed large cohort pooling projects, evaluating effects of baseline or usual exposure to metabolic risks on ischemic heart disease (IHD), hypertensive heart disease (HHD), stroke, diabetes, and, as relevant selected other CVDs, after adjusting for important confounders. We pooled all data to estimate relative risks (RRs) for each risk factor and examined effect modification by age or other factors, using random effects models.</p><p>Results</p><p>Across all risk factors, an average of 123 cohorts provided data on 1.4 million individuals and 52,000 CVD events. Each metabolic risk factor was robustly related to CVD. At the baseline age of 55–64 years, the RR for 10 mmHg higher SBP was largest for HHD (2.16; 95% CI 2.09–2.24), followed by effects on both stroke subtypes (1.66; 1.39–1.98 for hemorrhagic stroke and 1.63; 1.57–1.69 for ischemic stroke). In the same age group, RRs for 1 mmol/L higher TC were 1.44 (1.29–1.61) for IHD and 1.20 (1.15–1.25) for ischemic stroke. The RRs for 5 kg/m<sup>2</sup> higher BMI for ages 55–64 ranged from 2.32 (2.04–2.63) for diabetes, to 1.44 (1.40–1.48) for IHD. For 1 mmol/L higher FPG, RRs in this age group were 1.18 (1.08–1.29) for IHD and 1.14 (1.01–1.29) for total stroke. For all risk factors, proportional effects declined with age, were generally consistent by sex, and differed by region in only a few age groups for certain risk factor-disease pairs.</p><p>Conclusion</p><p>Our results provide robust, comparable and precise estimates of the effects of major metabolic risk factors on CVD and diabetes by age group.</p></div>", "links"=>[], "tags"=>["cardiovascular", "Coronary artery disease", "hypertension", "stroke", "Clinical research design", "Cohort studies", "Endocrinology", "Diabetic endocrinology", "epidemiology", "Cardiovascular disease epidemiology", "Epidemiological methods", "Global health", "Metabolic disorders", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Public health", "preventive medicine", "age-specific", "quantitative", "metabolic", "diseases", "pooled"], "article_id"=>759848, "categories"=>["Medicine"], "users"=>["Gitanjali M. Singh", "Goodarz Danaei", "Farshad Farzadfar", "Gretchen A. Stevens", "Mark Woodward", "David Wormser", "Stephen Kaptoge", "Gary Whitlock", "Qing Qiao", "Sarah Lewington", "Emanuele Di Angelantonio", "Stephen Vander Hoorn", "Carlene M. M. Lawes", "Mohammed K. Ali", "Dariush Mozaffarian", "Majid Ezzati"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0065174"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/The_Age_Specific_Quantitative_Effects_of_Metabolic_Risk_Factors_on_Cardiovascular_Diseases_and_Diabetes_A_Pooled_Analysis/759848", "title"=>"The Age-Specific Quantitative Effects of Metabolic Risk Factors on Cardiovascular Diseases and Diabetes: A Pooled Analysis", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-30 08:19:54"}

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Relative Metric

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