Characterization of Heat Index Experienced by Individuals Residing in Urban and Rural settings

Abstract

Background Heatwave warning systems rely on measurements taken at weather stations (WS), which do not reflect variation in temperature and humidity experienced by individuals moving through indoor and outdoor locations. We examined whether neighborhood measurement improved the prediction of individually experienced heat index in an urban vs. rural location.Methods Participants (residents of Birmingham, AL [N=89] and Wilcox County, AL [N=88]) wore thermometers clipped to their shoe for 7 days. Shielded thermometers/hygrometers were placed outdoors within participant’s neighborhoods (N=43). Nearest WS and neighborhood thermometers were matched to the participant's home address. Heat index (HI) was estimated from participant thermometer temperature and WS humidity per person-hour (HI[individual]), WS temperature and humidity (HI[WS]), or neighborhood temperature and humidity (HI[neighborhood]). Linear mixed models were fitted to determine the predictive value of WS and neighborhood HI for estimating HI[individual] in the urban and rural location.Results For all participants, a model with HI[neighborhood] alone explained the most variance in HI[individual]. A 1°C increase in HI[neighborhood] was associated with a 0.20°C [95%CI (0.19, 0.21) increase in HI[individual] in models adjusting for individual-level demographic factors. After adjusting for ambient condition differences, we found HI[individual] was heightened in the rural location compared to the urban location, particularly during non-rest hours (5am-midnight), when wind speed is higher, and on weekends. Both WS and neighborhood measurements underestimated the amount of time the participants experienced HI in the National Weather Service (NWS) Extreme Danger risk category compared to HI[individual]. Neighborhood measurements were better estimates of time spent in Danger and Extreme Danger NWS risk categories compared to WS.Conclusions Neighborhood measurements improved the prediction of individually-experienced HI, suggesting microclimates within neighborhoods are an important contributor to HI experienced by individuals.