GHDx: Dataset Records for Risk factors https://ghdx.healthdata.org/keywords/record-list/4293/feed en Global Burden of Disease Study (GBD) Alcohol Consumption and Ischemic Heart Disease Burden of Proof and Risk-Outcome Scores https://ghdx.healthdata.org/record/ihme-data/gbd-alcohol-ihd-bop-risk-outcome-scores <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">February, 2024 - February, 2024</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>Researchers systematically reviewed, identified, and extracted data from cohort, case-control, and Mendelian randomization studies published between 1970 and 2021 that estimated the association between alcohol consumption and risk of ischemic heart disease. In total, 124 unique studies were included. Relative risk curves for the association between alcohol consumption and ischemic heart disease were estimated using data from cohort and case-control studies separately and in combination, and from Mendelian randomization studies using the Burden of Proof meta-analytic framework.</p> </div> </div> </div> Thu, 15 Feb 2024 09:15:36 -0800 GHDx 540337 at https://ghdx.healthdata.org Palestine Multiple Indicator Cluster Survey 2019-2020 https://ghdx.healthdata.org/record/palestine-multiple-indicator-cluster-survey-2019-2020 <div class="field field-name-field-alt-title field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even">دولة فلسطين المسح العنقودي متعدد المؤشرات</div> </div> </div><div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">December, 2019 - January, 2020</div> </div> </div><span></span><div class="field field-name-field-secondary field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item"> <span><a href="/data-type/survey" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Survey</a>: </span> Cross-sectional - Household - Individual - Interview - Nationally representative - Subnationally representative - Urban-rural representative </div> </div> </div><div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/united-nations-childrens-fund-unicef" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">United Nations Children&#039;s Fund (UNICEF)</a></div> </div> </div> Tue, 30 Jan 2024 11:01:21 -0800 GHDx 464593 at https://ghdx.healthdata.org Global Burden of Disease (GBD) Cardiovascular Burden Estimates 1990-2022 https://ghdx.healthdata.org/record/ihme-data/cvd-1990-2022 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 1990 - December, 2022</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>This dataset includes total cardiovascular disease burden estimates globally for multiple cardiovascular diseases for 7 Global Burden of Disease Study (GBD) super regions, 21 GBD regions, 204 countries and territories, and select subnational locations. The following are reported: mortality by age and sex for the years 1990-2022; age-standardized mortality in 2022 by Socio-Demographic Index (SDI), a composite indicator of fertility, income, and education; all ages and age-standardized prevalence for 2022; and age-standardized disability-adjusted life years (DALYs) for 2022. The dataset also includes burden attributable to selected risk factors for each GBD region in 2022, as measured by DALYs. These data are custom calculated for publication in the Journal of the American College of Cardiology and will not be available in the GBD 2022 Results Tool.</p> </div> </div> </div> Thu, 14 Dec 2023 15:30:01 -0800 GHDx 540398 at https://ghdx.healthdata.org Global Burden of Disease Study 2019 (GBD 2019) Burden by Risk 1990-2019 https://ghdx.healthdata.org/record/ihme-data/gbd-2019-burden-by-risk-1990-2019 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 1990 - December, 2019</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.</p> <p>Annual deaths, YLLs, YLDs, and DALYs attributable to 87 risk factors as well as estimates for summary exposure values (SEVs) by risk are available from the <strong><a href="//ghdx.healthdata.org/gbd-results-tool">GBD Results Tool</a></strong>. Estimates are available by age and sex for 1990-2019. Select tables published in <em>The Lancet</em> in October 2020 in "Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019" are also available for download via the “Files” tab above.</p> <p>For additional GBD results and resources, visit the <strong><a href="//ghdx.healthdata.org/gbd-2019">GBD 2019 Data Resources page</a></strong>.</p> </div> </div> </div> Fri, 03 Mar 2023 16:37:13 -0800 GHDx 442374 at https://ghdx.healthdata.org Global Burden of Disease (GBD) Cardiovascular Burden Estimates 1990 and 2021 https://ghdx.healthdata.org/record/ihme-data/cvd-1990-2021 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 1990 - December, 2021</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>This dataset includes total cardiovascular disease burden estimates globally for multiple cardiovascular diseases for 7 Global Burden of Disease Study (GBD) super regions, 21 GBD regions, 204 countries and territories, and select subnational locations. The following are reported: mortality by age and sex for the years 1990 and 2021; age-standardized mortality in 2021 by Socio-Demographic Index (SDI), a composite indicator of fertility, income, and education; all ages and age-standardized prevalence for 2021; and age-standardized disability-adjusted life years (DALYs) for 2021. The dataset also includes burden attributable to selected risk factors for each GBD region in 2021, as measured by DALYs. These data are custom calculated for publication in the Journal of the American College of Cardiology and will not be available in the GBD 2021 Results Tool.</p> </div> </div> </div> Tue, 13 Dec 2022 06:48:15 -0800 GHDx 508123 at https://ghdx.healthdata.org United States Health-Care Spending Attributable to Modifiable Risk Factors 2016 https://ghdx.healthdata.org/record/ihme-data/united-states-health-care-spending-attributable-modifiable-risk-factors-2016 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 2016 - December, 2016</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>This dataset is the result of a study to quantify health-care spending attributable to modifiable risk factors in the United States of America for 2016. Data from two existing studies were used to produce the estimates. The first dataset is the <a href="//ghdx.healthdata.org/record/ihme-data/united-states-health-care-spending-payer-and-health-condition-1996-2016">Institute for Health Metrics and Evaluation’s Disease Expenditure Study 2016</a>, from which estimates of US health-care spending by condition, age, and sex were extracted. These results were merged with population attributable fraction estimates for 84 modifiable risk factors from the <a href="//ghdx.healthdata.org/record/ihme-data/gbd-2017-burden-risk-1990-2017">Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017</a>. Estimates were produced for spending by 14 aggregate conditions attributable to 19 risk factors. The estimates are by sex and 5 age groups and reported in 2016 US dollars.</p> </div> </div> </div> Sat, 12 Mar 2022 12:39:07 -0800 GHDx 457038 at https://ghdx.healthdata.org United States COVID-19 Scenarios 2020-2021 https://ghdx.healthdata.org/record/ihme-data/united-states-covid-19-scenarios-2020-2021 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">February, 2020 - February, 2021</div> </div> </div><span></span><div class="field field-name-field-secondary field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item"> <span><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a>: </span> Subnationally representative </div> </div> </div><div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>This dataset represents estimates of the ongoing COVID-19 pandemic across the 50 U.S. States and DC through 28th February 2021. Projections for total and daily deaths, daily infections, and testing are included with hospital resource use statistics. In total five scenarios are presented: a 'plausible reference scenario,' which assumes social distancing mandates are re-imposed for 6 weeks when a threshold daily death rate of 8 per million is reached; a 'mandates easing' scenario, where mandates are not re-imposed; a 'universal mask-use' scenario, where mask utilization reaches 95% usage in public in every location; a less comprehensive mask scenario of 85% public use of masks (‘plausible reference + 85% mask-use’ scenario); and a scenario of universal mask wearing in the absence of any additional NPI (‘mandate easing + universal mask use’). These projections are produced with a model that incorporates data on observed COVID-19 deaths, hospitalizations, and cases, as well as multiple covariates.</p> </div> </div> </div> Sat, 12 Mar 2022 12:39:07 -0800 GHDx 457630 at https://ghdx.healthdata.org Mortality Burden Attributable to Non-Optimal Temperature 1990-2019 https://ghdx.healthdata.org/record/ihme-data/mortality-burden-attributable-non-optimal-temperature-1990-2019 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 1990 - December, 2019</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>This dataset contains estimates for deaths and years of life lost (YLLs) attributable to non-optimal temperature exposure (including high temperature, low temperature, and the aggregate non-optimal temperature risk) for 204 countries, Global Burden of Disease Study (GBD) regions and super regions, and globally for the years 1990, 2010, and 2010. These estimates inform a paper published in <em>The Lancet</em> in August 2021 titled “Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study.”</p> </div> </div> </div> Sat, 12 Mar 2022 12:38:46 -0800 GHDx 488989 at https://ghdx.healthdata.org Tuberculosis Household Risk Exposure Estimates 2019 https://ghdx.healthdata.org/record/ihme-data/tuberculosis-household-risk-exposure-estimates-2019 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">January, 2019 - December, 2019</div> </div> </div> <div class="field field-name-field-type field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item even"><a href="/data-type/estimate" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Estimate</a></div> </div> </div> <div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>This dataset contains estimates for the number of persons with exposure to household incident pulmonary tuberculosis (TB) for 20 high-incidence TB countries in 2019 (as determined by Global Burden of Disease (GBD) Study 2019 estimates). Estimates were produced using pulmonary TB incidence from the GBD 2019 and location-specific household structure data from Demographic Health Surveys (DHS) and Integrated Public Use Microdata Series (IPUMs). Estimates include mean and 95% uncertainty intervals for both sexes disaggregated by age groups.</p> <p>These estimates inform a paper published in <em>EclinicalMedicine </em>in November 2021 titled “Estimating the population at high risk for tuberculosis through household exposure in high-incidence countries: a model-based analysis.”</p> </div> </div> </div> Sat, 12 Mar 2022 12:39:03 -0800 GHDx 492204 at https://ghdx.healthdata.org Brazil HealthRise Household Survey 2017 https://ghdx.healthdata.org/record/ihme-data/brazil-healthrise-household-survey-2017 <div class="field field-name-field-time field-type-datetime field-label-hidden"> <div class="field-items"> <div class="field-item even">October, 2017 - December, 2017</div> </div> </div><span></span><div class="field field-name-field-secondary field-type-taxonomy-term-reference field-label-hidden"> <div class="field-items clearfix"> <div class="field-item"> <span><a href="/data-type/survey" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Survey</a>: </span> Cross-sectional - Household - Individual - Interview </div> </div> </div><div class="field field-name-field-provider field-type-taxonomy-term-reference field-label-inline clearfix"> <div class="field-label">Provider&nbsp;</div> <div class="field-items"> <div class="field-item even"><a href="/organizations/institute-health-metrics-and-evaluation-ihme" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Institute for Health Metrics and Evaluation (IHME)</a></div> </div> </div> <div class="field field-name-field-summary field-type-text field-label-hidden"> <div class="field-items"> <div class="field-item even"><p>HealthRise is a collaborative multicountry initiative to implement and evaluate innovative community-based programs intended to improve heart disease and diabetes care in underserved communities. Conducted as part of HealthRise Brazil, this household survey was carried out in approximately 2,000 households in Padre Paraíso in the state of Minas Gerais and Poções in the state of Bahia. Data were collected regarding sociodemographic background, risk factors, medical history, and knowledge, attitudes, and practices related to NCDs. Anthropometric data, including height, weight, and abdominal circumference were also collected, in addition to blood pressure and random blood glucose (RBG) measurements. The data were collected through computer-assisted personal interviews (CAPI) with one adult age 30 years or older in each household.</p> </div> </div> </div> Sat, 12 Mar 2022 12:37:35 -0800 GHDx 432116 at https://ghdx.healthdata.org