This is the code and data for an R Shiny dashboard, which is associated with the manuscript 'Urban Heat Island Impacts on Heat-Related Cardiovascular Morbidity: A Time Series Analysis of Older Adults in US Metropolitan Areas'. The dashboard is an interactive supplemental material and allows for interaction with the manuscript's primary results - the heat-related cardiovascular risk and burden across the urban cores of 120 contiguous US metropolitan statistical areas (MSAs), 2000-2017, for the entire study population, different subpopulations, and in low and high urban heat island intensity (UHII) areas. It also allows for interaction with the MSA-level heat-related risk and burden, overall and in low and high UHII areas, and exploration of the ZIP code-level temperature, UHII, and Medicare hospitalization data used in the analyses. The dashboard displays a variety of interactive tables and figures and the results displayed in the dashboard can be downloaded. Details on the datasets and methods used as well as a discussion of all results and sensitivity analyses can be found in the associated manuscript. At present, the dashboard can be viewed here: https://rstudio-connect.dmap-stage.aws.epa.gov/content/c0b492eb-2c37-4018-a0d3-a4563b9add51/. For any questions, please email: [email protected] or [email protected].
The United States (US) population largely resides in metropolitan areas experiencing urban heat islands (UHIs) and climate change-driven temperature increases. Extreme heat has been linked to increased cardiovascular disease (CVD) risk, yet little is known about how this association varies between cities or with UHI intensity (UHII). We aimed to identify the US urban populations most at-risk of and burdened by heat-related CVD morbidity while considering the role of UHII. ZIP code-level daily counts of CVD hospitalizations among Medicare enrollees, aged 65-114, were obtained for 120 US metropolitan statistical areas (MSAs) between 2000-2017. Local average temperatures were estimated by interpolating daily weather station observations. ZIP codes were stratified into low and high UHII areas using the first and fourth UHII quartiles with an equal number of hospitalizations. MSA-specific associations between temperature and hospitalization were estimated using quasi-Poisson regression with distributed lag non-linear models and pooled via multivariate meta-analyses. Stratified analyses were performed by age, sex, race, and chronic condition status in low and high UHII areas. We also calculated the CVD hospitalizations attributable to heat. Extreme heat (MSA-specific 99th percentile, ~28.6°C) increased CVD hospitalization risk by 1.5% (95% CI: 0.4%, 2.6%), with considerable variation among MSAs. Between 2000-2017, there were an estimated 37,028 (95% CI: 35,741, 37,988) heat-attributable admissions, with most due to extreme temperatures. Risk in high UHII areas (2.4% [95% CI: 0.4%, 4.3%]) exceeded that in low UHII areas (1.0% [95% CI: -0.8%, 2.8%]). High UHII areas accounted for 35% of the total heat-related burden and disproportionately impacted already heat-vulnerable populations. The most at-risk and burdened populations were females, individuals aged 75-114, those with chronic kidney disease or diabetes living in high UHII areas. Overall, extreme heat increased cardiovascular morbidity risk and burden among older urban populations. UHIs exacerbated these heat-related impacts, especially among those with existing vulnerabilities.
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