The Burden of Cardiovascular Diseases Among US States, 1990-2016

Key Points Question How does the total burden of cardiovascular diseases vary across US states? Findings In this study using the Global Burden of Disease methodology, large disparities in total burden of CVD were found between US states despite marked improvements in CVD burden. Meaning These estimates can provide a benchmark for states working to focus on key risk factors, improve health care quality, and lower health care costs.

ICD8, 9, and 10 codes were mapped to GBD causes. Nonspecific or intermediate causes of death inappropriately assigned as underlying causes of death were redistributed to appropriate underlying causes using an algorithm developed for the GBD study. After identifying nonspecific or intermediate codes (for example generalized atherosclerosis or left-sided heart failure), a regression model was used to reassign these codes to biologically plausible targets. All-cause, all-cardiovascular, and cause-specific mortality was estimated using the Cause of Death Ensemble Model (CODEm) which produces causespecific smoothed trends over time by age, sex, and state. Atrial fibrillation mortality was estimated with a separate natural history model described below. The CODCorrect algorithm was applied to ensure that cause-specific, cardiovascular, and all-cause deaths were consistent. Years of life lost (YLLs) were computed by multiplying the number of deaths from each cause in each age group by a global reference life expectancy at the average of age of death among those who died in the age group.

eMethods 4. Nonfatal modeling methods
Nonfatal estimates for cardiovascular diseases were modeled using the DisMod-MR 2.1 platform. Morbidity modeling methods have been documented elsewhere 2 . A list of covariates used in DisMod modeling for each CVD cause can be found in Appendix Table 3b. Appendix Table 4 includes a list of International Classification of Diseases (ICD) codes used in the extraction of hospital and claims data, mapped to specific cardiovascular diseases.

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List the funding sources for the work.
Funding sources listed at end of paper.

Funding Sources Data Inputs
For all data inputs from multiple sources that are synthesized as part of the study: 3 Describe how the data were identified and how the data were accessed.
Narrative description of data seeking methodology provided in previously published appendices. Narrative about inclusion and exclusion criteria by data type provided in previously published appendices.
1) GBD 2016 Causes of Death Collaborators. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 2017: 390;1151-210. 2) GBD 2016 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 2017: 390;1211-59. 3) GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 2017: 390;1345-1422 Provide information on all included data sources and their main characteristics. For each data source used, report reference information or contact name/institution, population represented, data collection method, year(s) of data collection, sex and age range, diagnostic criteria or measurement method, and sample size, as relevant.
Interactive, online data source tool that provides metadata for data sources by component, geography, cause, risk, or impairment has been developed.
Online data tools: http://ghdx.healthdata.org/gbd-2016/data-input-sources 6 Identify and describe any categories of input data that have potentially important biases (e.g., based on characteristics listed in item 5).
Summary of known biases by cause included in methodological approaches sections of previously published appendices. For data inputs that contribute to the analysis but were not synthesized as part of the study: 7 Describe and give sources for any other data inputs. Included in list of all data sources provided on online data source tool.
Online data tools: http://ghdx.healthdata.org/gbd-2016/data-input-sources For all data inputs: 8 Provide all data inputs in a file format from which data can be efficiently extracted (e.g., a spreadsheet as opposed to a PDF), including all relevant meta-data listed in item 5. For any data inputs that cannot be shared due to ethical or legal reasons, such as third-party ownership, provide a contact name or the name of the institution that retains the right to the data.
Downloads of input data will be available through online tools, including data visualization tools and data query tools. Input data not available in tools will be made available upon request.