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Weather-related effects among hemodialysis patients in selected urban northeast cities: preliminary findings from the HEAT-HD study

Presenting Author: Richard Remigio, MPhil, MS, University of Maryland, Drexel University Urban Health Collaborative

ABSTRACT

Background: Many studies on heat and health have shown adverse effects within the general population especially within urban regions. However, there is less focused work on heat vulnerability among populations living with end-stage renal disease (ESRD).

Objectives: In this study, we determined the effects of outdoor weather conditions among patients receiving hemodialysis, a long-term form of treatment that manages ESRD, in selected urban northeastern cities in the United States: Boston, New York, and Philadelphia. Measures of interest included inter-dialytic weight gain (IDWG) percentage and blood pressure (each before treatment), and mortality and hospitalization events.

Methods: We joined local meteorological and patient-level data with respect to location. Random effects modeling quantified the association between single-day extreme heat events with clinical measurements. Case-crossover analyses were used for mortality & hospitalization events. We tested same-day and one-day lag extreme heat exposures to estimate time-varying effects among patients.

Results: During same-day heat wave events across all three cities, we found that on average individual-level IDWG percentage decreased between 0.18 to 0.34 %, whereas systolic blood pressure decreased between 2.61 to 3.28 mm Hg. We estimated 55- to 98-percent increased mortality risk attributed to one-day lag extreme heat event in all three cities. On hospitalization, single-day heat events generally did not demonstrate a significant association.

Implications: Preliminary findings demonstrated potential heat effects on individuals living with ESRD. Clinical measurements appear to respond to elevated outdoor temperature. Further work is needed to account for regional-specific and socio-demographic confounding biases.

Authors: Richard Remigio, MPhil, MS; Alice Topping; Jochen Raimann, MD, PhD; Peter Kotanko, MD; Frank W. Maddux, MD, FACP; and Patrick Kinney, PhD.