Ozone, Heat Wave, and Cardiovascular Disease Mortality: A Population-Based Case-Crossover Study.

A case-crossover study among 511,767 cardiovascular disease (CVD) deaths in Jiangsu province, China, during 2015-2021 was conducted to assess the association of exposure to ambient ozone (O3) and heat wave with CVD mortality and explore their possible interactions. Heat wave was defined as extreme high temperature for at least two consecutive days. Grid-level heat waves were defined by multiple combinations of apparent temperature thresholds and durations. Residential O3 and heat wave exposures were assessed using grid data sets (spatial resolution: 1 km × 1 km for O3; 0.0625° × 0.0625° for heat wave). Conditional logistic regression models were applied for exposure-response analyses and evaluation of additive interactions. Under different heat wave definitions, the odds ratios (ORs) of CVD mortality associated with medium-level and high-level O3 exposures ranged from 1.029 to 1.107 compared with low-level O3, while the ORs for heat wave exposure ranged from 1.14 to 1.65. Significant synergistic effects on CVD mortality were observed for the O3 and heat wave exposures, which were generally greater with higher levels of the O3 exposure, higher temperature thresholds, and longer durations of heat wave exposure. Up to 5.8% of the CVD deaths were attributable to O3 and heat wave. Women and older adults were more vulnerable to the exposure to O3 and heat wave exposure. Exposure to both O3 and heat wave was significantly associated with an increased odds of CVD mortality, and O3 and heat wave can interact synergistically to trigger CVD deaths.

The impact of apparent temperature on the emergency visits for traumatic fractures in Hangzhou, China.

BACKGROUND: Traumatic fractures occur frequently worldwide. However, research remains limited on the association between short-term exposure to temperature and traumatic fractures. This study aims to explore the impact of apparent temperature (AT) on emergency visits (EVs) due to traumatic fractures. METHODS: Based on EVs data for traumatic fractures and the contemporary meteorological data, a generalized Poisson regression model along with a distributed lag nonlinear model (DLNM) were undertaken to determine the impact of AT on traumatic fracture EVs. Subgroup analysis by gender and age and sensitivity analysis were also performed. RESULTS: A total of 25,094 EVs for traumatic fractures were included in the study. We observed a wide "J"-shaped relationship between AT and risk of traumatic fractures, with AT above 9.5 °C positively associated with EVs due to traumatic fractures. The heat effects became significant at cumulative lag 0-11 days, and the relative risk (RR) for moderate heat (95th percentile, 35.7 °C) and extreme heat (99.5th percentile, 38.8 °C) effect was 1.311 (95% CI: 1.132-1.518) and 1.418 (95% CI: 1.191-1.688) at cumulative lag 0-14 days, respectively. The cold effects were consistently non-significant on single or cumulative lag days across 0-14 days. The heat effects were higher among male and those aged 18-65 years old. The sensitivity analysis results remained robust. CONCLUSION: Higher AT is associated with cumulative and delayed higher traumatic fracture EVs. The male and those aged 18-65 years are more susceptible to higher AT.

Effects of apparent temperature on hospitalization rates for cardiovascular diseases: a case study of different rural areas in Northwest China.

Apparent temperature (AT) is a composite index that combines ambient temperature, humidity, wind speed and other meteorological factors, and reflects heat perception more accurately than raw temperature. This is the first study to investigate the association between AT and CVD in rural areas of Jiuquan and Longnan, Gansu Province, China. In this study, the distributed lag nonlinear model (DLNM) was used to examine the exposure-response relationship between AT and the 21 days relative risk (RR) of CVD admission. The results showed that the exposure risk of the gender group in Jiuquan was opposite to that of Longnan under the influence of cold effect. Under the influence of heat effect, it has a protective effect on all groups in Jiuquan area, which is harmful to males and adults in Longnan area. The results of this study can help local governments to formulate public policies.

Cardiovascular admission risk attributable to hot apparent temperature: a study in a rural area of northwest China.

Cardiovascular disease (CVD) is the leading cause of mortality worldwide, posing a significant threat to public health. Research on the relationship between CVD and temperature has primarily focused on developed urban settings, with limited studies conducted in rural regions with lower levels of development. Additionally, compared to relative risks, attributable risks can provide more information when assessing the risk of CVD hospitalizations associated with exposure to apparent temperature (AT). Apparent temperature is a composite temperature index that takes into account both meteorological factors and temperature, providing an objective reflection of human thermal sensation. Therefore, this study investigates the impact of AT on CVD hospitalization and quantifies the burden of CVD admission in the rural areas of China. We employed the distributed lag non-linear model (DLNM) to estimate the relationship between AT and the relative risk (RR) of CVD hospitalization. Finally, we used attributable risk methods to quantify this relationship further.

Field temperature performances of in-use permeable sidewalks and asphalt vehicle roads and the potential impacts on apparent temperature and land surface temperature.

Permeable pavements help reduce surface temperatures and have been widely implemented in urban areas. This study utilized an in-use permeable pavement sidewalk in front of a mass rapid transit station in the Taipei city center of Taiwan to determine the actual pavement surface temperature performance. A neighboring asphalt road and impervious pavement were also monitored. With a full year of continuous monitoring, the results showed that the temperature of permeable pavement was 3.7 °C lower than that of impervious pavement and 4.5 °C lower than that of asphalt pavement in the hot season. The frequent rainfall in spring resulted in the smallest temperature differences between the different pavement types. The cooling effects of permeable pavement differed at the different air temperatures. At air temperatures lower than 15 °C, the differences among pavement surface temperatures were noticeable. However, when the air temperature was higher than 35 °C, the surface temperature of permeable pavement was not different from that of impervious pavement and was greater than 55 °C. Field observations were carried out to determine the effects on the apparent temperature and the future surface temperature of climate change scenarios. The results showed that permeable pavement could reduce the average apparent temperature to near the air temperature, and asphalt pavement could increase the apparent temperature by 1.2 °C, assuming that the pavement temperature completely affects the air temperature. With the good prediction ability of the machine learning approach and 15 environmental factors, the preliminary prediction showed the projected surface temperature change in Taipei city in 2033. In the worst-case scenario, the average impervious pavement temperature is as high as 39.12 °C, whereas the average permeable pavement temperature is 32.50 °C.

Effects of apparent temperature on daily outpatient and inpatient visits for cause-specific respiratory diseases in Ganzhou, China: a time series study.

BACKGROUND: Non-optimum temperatures are associated with increased risk of respiratory diseases, but the effects of apparent temperature (AT) on respiratory diseases remain to be investigated. METHODS: Using daily data from 2016 to 2020 in Ganzhou, a large city in southern China, we analyzed the impact of AT on outpatient and inpatient visits for respiratory diseases. We considered total respiratory diseases and five subtypes (influenza and pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma and chronic obstructive pulmonary disease [COPD]). Our analysis employed a distributed lag nonlinear model (DLNM) combined with a generalized additive model (GAM). RESULTS: We recorded 94,952 outpatients and 72,410 inpatients for respiratory diseases. We found AT significantly non-linearly associated with daily outpatient and inpatient visits for total respiratory diseases, influenza and pneumonia, and URTI, primarily during comfortable AT levels, while it was exclusively related with daily inpatient visits for LRTI and COPD. Moderate heat (32.1 °C, the 75.0th centile) was observed with a significant effect on both daily outpatient and inpatient visits for total respiratory diseases at a relative risk of 1.561 (1.161, 2.098) and 1.276 (1.027, 1.585), respectively (both P < 0.05), while the results of inpatients became insignificant with the adjustment for CO and O3. The attributable fractions in outpatients and inpatients were as follows: total respiratory diseases (24.43% and 18.69%), influenza and pneumonia (31.54% and 17.33%), URTI (23.03% and 32.91%), LRTI (37.49% and 30.00%), asthma (9.83% and 3.39%), and COPD (30.67% and 10.65%). Stratified analyses showed that children ≤5 years old were more susceptible to moderate heat than older participants. CONCLUSIONS: In conclusion, our results indicated moderate heat increase the risk of daily outpatient and inpatient visits for respiratory diseases, especially among children under the age of 5.

Spatio-temporal interpolation and delineation of extreme heat events in California between 2017 and 2021.

Robust spatio-temporal delineation of extreme climate events and accurate identification of areas that are impacted by an event is a prerequisite for identifying population-level and health-related risks. In prior research, attributes such as temperature and humidity have often been linearly assigned to the population of the study unit from the closest weather station. This could result in inaccurate event delineation and biased assessment of extreme heat exposure. We have developed a spatio-temporal model to dynamically delineate boundaries for Extreme Heat Events (EHE) across space and over time, using a relative measure of Apparent Temperature (AT). Our surface interpolation approach offers a higher spatio-temporal resolution compared to the standard nearest-station (NS) assignment method. We show that the proposed approach can provide at least 80.8 percent improvement in identification of areas and populations impacted by EHEs. This improvement in average adjusts the misclassification of about one million Californians per day of an extreme event, who would be either unidentified or misidentified under EHEs between 2017 and 2021.

Temperature modifies the association between air pollution and respiratory disease mortality in Cape Town, South Africa.

The aim of this 10-year study was to investigate whether and how temperature modifies the association between daily ambient PM10, NO2, SO2 air pollution and daily respiratory disease mortality in Cape Town. A time-stratified case-crossover epidemiological design was applied. Susceptibility by sex and age groups (15-64 years and ≥65 years) was also investigated. On days with medium Tapp levels, NO2 displayed a stronger association with respiratory mortality than PM10 or SO2. Females appeared to be more susceptible to NO2 at medium Tapp levels to males. The 15-64-year-old age group seemed to be more vulnerable to NO2 and PM10 at medium Tapp levels compared to the elderly (≥65 years). At high Tapp levels, females were more susceptible to PM10. The 15-64-year-old group were more vulnerable to NO2 and SO2. The results can be used in present-day early warning systems and in risk assessments to estimate the impact of increased air pollution and temperature.

Thermodynamic assessment of heat stress in dairy cattle: lessons from human biometeorology.

A versatile meteorological index for predicting heat stress in dairy cattle remains elusive. Despite numerous attempts at developing such indices and widespread use of some, there is growing skepticism about the accuracy and adequacy of the existing indices as well as the general statistical approach used to develop them. At the same time, precision farming of high-yielding animals in a drastically changing climate calls for more effective prediction and alleviation of heat stress. The present paper revisits classical work on human biometeorology, particularly the apparent temperature scale, to draw inspiration for advancing research on heat stress in dairy cattle. The importance of a detailed, mechanistic understanding of heat transfer and thermoregulation is demonstrated and reiterated. A model from the literature is used to construct a framework for identifying and characterizing conditions of potential heat stress. New parameters are proposed to translate the heat flux calculations based on heat-balance models into more tangible and more useful meteorological indices, including an apparent temperature for cattle and a thermoregulatory exhaustion index. A validation gap in the literature is identified as the main hindrance to the further development and deployment of heat-balance models. Recommendations are presented for systematically addressing this gap in particular and continuing research within the proposed framework in general.

Climate change and physical activity: ambient temperature and urban trail use in Texas.

Individuals in the USA are insufficiently active, increasing their chronic disease risk. Extreme temperatures may reduce physical activity due to thermal discomfort. Cooler climate studies have suggested climate change may have a net positive effect on physical activity, yet research gaps remain for warmer climates and within-day physical activity patterns. We determined the association between ambient temperatures (contemporary and projected) and urban trail use in a humid subtropical climate. At a trail in Austin, TX, five electronic counters recorded hourly pedestrian and cyclist counts in 2019. Weather data were acquired from World Weather Online. Generalized additive models estimated the association between temperature and trail counts. We then combined the estimated exposure-response relation with weather projections from climate models for intermediate (RCP4.5) and high (RCP8.5) emissions scenarios by NASA NEX-GDDP. From summer to autumn to spring to winter, hourly trail counts shifted from bimodal (mid-morning and early-evening peaks) to one mid-day peak. Pedestrians were more likely to use the trail between 7 and 27 °C (45-81°F) with peak use at 17 °C (63°F) and cyclists between 15 and 33 °C (59-91°F) with peak use at 27 °C (81°F) than at temperature extremes. A net decrease in trail use was estimated by 2041-2060 (RCP4.5: pedestrians = - 4.5%, cyclists = - 1.1%; RCP8.5: pedestrians = - 6.6%, cyclists = - 1.6%) and 2081-2100 (RCP4.5: pedestrians = - 7.5%, cyclists = - 1.9%; RCP8.5: pedestrians = - 16%, cyclists = - 4.5%). Results suggest climate change may reduce trail use. We recommend interventions for thermal comfort at settings for physical activity.

Does surrounding greenness moderate the relationship between apparent temperature and physical activity? Findings from the PHENOTYPE project.

BACKGROUND: Physical activity can be affected by both meteorological conditions and surrounding greenness, but few studies have evaluated the effects of these environmental factors on physical activity simultaneously. This multi-city comparative study aimed to assess the synergetic effects of apparent temperature and surrounding greenness on physical activity in four European cities. Specifically, we aimed to identify an interaction between surrounding greenness and apparent temperature in the effects on physical activity. METHODS: Data were collected from 352 adult residents of Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands), and Kaunas (Lithuania) as part of the PHENOTYPE study. Participants wore a smartphone for seven consecutive days between May-December 2013 and provided additional sociodemographic survey data. Hourly average physical activity (Metabolic Equivalent of Task (MET)) and surrounding greenness (NDVI) were derived from the Calfit mobile application collecting accelerometer and location data. Hourly apparent temperature was calculated from temperature and relative humidity, which were obtained from local meteorological stations along with other meteorological covariates (rainfall, windspeed, and sky darkness). We assessed the interaction effects of apparent temperature and surrounding greenness on hourly physical activity for each city using linear mixed models, while adjusting for meteorological, demographic, and time-related variables. RESULTS: We found significant interactions between apparent temperature and surrounding greenness on hourly physical activity in three of four cities, aside from the coastal city of Barcelona. Significant quadratic effects of apparent temperature were found in the highest level of surrounding greenness for Stoke-on-Trent and Doetinchem, with 4% decrease in median MET observed for a 10°C departure from optimal temperature (15.2°C and 14.6°C, respectively). Significant linear effects were found for higher levels of surrounding greenness in Kaunas, whereby an increase of 10°C was associated with ∼4% increase in median MET. CONCLUSION: Apparent temperature and surrounding greenness interacted in the effect on hourly physical activity across three of four European cities, with varying effect between cities. While quadratic effects of temperature suggest diminishing levels of physical activity in the highest greenness levels in cities of temperate climates, the variation in surrounding greenness between cities could be further explored, particularly by looking at indoor-outdoor locations. The study findings support the need for evidence-based physical activity promotion and urban design.

Heat wave intensity and daily mortality in four of the largest cities of Spain.

In the current context of climate change, heat waves have become a significant problem for human health. This study assesses the effects of heat wave intensity on mortality (natural, respiratory and cardiovascular causes) in four of the largest cities of Spain (Barcelona, Bilbao, Madrid and Seville) during the period between 1990 and 2014. To model the heat wave severity the Excess Heat Factor (EHF) was used. The EHF is a two-component index. The first is the comparison of the three-day average daily mean temperature with the 95th percentile. The second component is a measure of the temperatures reached during the three-day period compared with the recent past (the previous 30 days). The city-specific exposure-response curves showed a non-linear J-shaped relationship between mortality and the EHF. Overall city-specific mortality risk estimates in natural causes for 1st vs. 99th percentile increases range from the highest mortality risk with 2.73 (95% CI: 2.34-3.18) in Seville to a risk of 1.78 (95% CI: 1.62-1.97) and 1.78 (95% CI: 1.45-2.19) in Barcelona and Bilbao, respectively. When we compare our results with risk estimates for the analyzed Spanish cities in other studies, the heat wave related mortality risks seem to be clearly higher. Furthermore, it has been demonstrated that different heat wave days of the same event do not present the same degree of severity/intensity. Thus, the intensity of a heat wave is an important mortality risk indicator during heat wave days. Due to the low number of studies on the EHF as a heat wave intensity indicator and heat-related mortality and morbidity, further research is required to validate its application in other geographic areas and focus populations.

A time series analysis of the relationship between apparent temperature, air pollutants and ischemic stroke in Madrid, Spain.

The understanding of the role of environment on the pathogenesis of stroke is gaining importance in the context of climate change. This study analyzes the temporal pattern of ischemic stroke (IS) in Madrid, Spain, during a 13-year period (2001-2013), and the relationship between ischemic stroke (admissions and deaths) incidence and environmental factors on a daily scale by using a quasi-Poisson regression model. To assess potential delayed and non-linear effects of air pollutants and Apparent Temperature (AT), a biometeorological index which represents human thermal comfort on IS, a lag non-linear model was fitted in a generalized additive model. The mortality rate followed a downward trend over the studied period, however admission rates progressively increased. Our results show that both increases and decreases in AT had a marked relationship with IS deaths, while hospital admissions were only associated with low AT. When analyzing the cumulative effects (for lag 0-14 days), with an AT of 1.7 °C (percentile 5%) a RR of 1.20 (95% CI, 1.05-1.37) for IS mortality and a RR of 1.09 (95% CI, 0.91-1.29) for morbidity is estimated. Concerning gender differences, men show higher risks of mortality in low temperatures and women in high temperatures. No significant relationship was found between air pollutant concentrations and IS morbi-mortality, but this result must be interpreted with caution, since there are strong spatial fluctuations of the former between nearby geographical areas that make it difficult to perform correlation analyses.

Effect of apparent temperature on daily emergency admissions for mental and behavioral disorders in Yancheng, China: a time-series study.

BACKGROUND: Very few studies have focused on the relationship between ambient apparent temperature (AT) and admission of mental and behaviour disorders (MDs). Therefore, a time-series study was conducted in Yancheng, China, to explore the effects of AT on the daily emergency admissions of patients with MDs over the period of 2014-17. METHODS: A quasi-Poisson generalized linear model (GLM) combined with a distributed lag non-linear model (DLNM) was adopted to explore the associations after adjusting for time trend, day of the week, humidity, sunshine duration, rainfall, holidays and air pollutants. In the subgroup analysis, the modification effects of age and sex were also examined. RESULTS: Overall, 8438 cases of MDs emergency admissions were identified. With the apparent temperature with the minimum number of admissions (- 3.4 °C) serving as a reference, a positive correlation emerged between high AT and daily emergency admissions of patients with MDs in Yancheng, China, with the lagged effect of 1 to 5 days. The subgroup analysis demonstrated a positive relationship between AT and MDs emergency admissions among males and individuals younger than 45 years old, with no lagged effect. CONCLUSIONS: The results will provide important scientific evidence for mental health policy-makers and practitioners for possible intervention, especially among the vulnerable populations.

Relationship among environmental quality variables, housing variables, and residential needs: a secondary analysis of the relationship among indoor, outdoor, and personal air (RIOPA) concentrations database.

Retrospective descriptive secondary analyses of data from relationships of indoor, outdoor, and personal air (RIOPA) study homes (in Houston, Texas; Los Angeles County, California; and, Elizabeth, New Jersey May 1999-February 2001) were conducted. Data included air exchange rates, associations between indoor and outdoor temperature and humidity, and calculated apparent temperature and humidex. Analyses examined if study homes provided optimum thermal comfort for residents during both heating and cooling seasons when compared to current American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) Standards 62/62.1 and 55. Results suggested outdoor temperature, humidex, and apparent temperature during the cooling season potentially served as indicators of indoor personal exposure to parameters of thermal comfort. Outdoor temperatures, humidex, and apparent temperature during the cooling season had statistically significant predictive abilities in predicting indoor temperature. During the heating season, only humidex in Texas and combined data across study states were statistically significant, but with weaker to moderate predicative ability. The high degree of correlation between outdoor and indoor environmental variables provided support for the validity of epidemiologic studies of weather relying on temporal comparisons. Results indicated most RIOPA study residents experienced thermal comfort; however, many values indicated how several residents may have experienced some discomfort depending on clothing and indoor activities. With climate change, increases in temperature are expected, with more days of extreme heat and humidity and, potentially harsher, longer winters. Homes being built or modernized should be created with the appropriate guidelines to provide comfort for residents daily and in extreme weather events.

Genetic programming-based mathematical modeling of influence of weather parameters in BOD5 removal by Lemna minor.

This study, through extensive experiments and mathematical modeling, reveals that other than retention time and wastewater temperature (Tw), atmospheric parameters also play important role in the effective functioning of aquatic macrophyte-based treatment system. Duckweed species Lemna minor is considered in this study. It is observed that the combined effect of atmospheric temperature (Tatm), wind speed (Uw), and relative humidity (RH) can be reflected through one parameter, namely the "apparent temperature" (Ta). A total of eight different models are considered based on the combination of input parameters and the best mathematical model is arrived at which is validated through a new experimental set-up outside the modeling period. The validation results are highly encouraging. Genetic programming (GP)-based models are found to reveal deeper understandings of the wetland process.

Modeling of constructed wetland performance in BOD5 removal for domestic wastewater under changes in relative humidity using genetic programming.

Despite the extensive use of constructed wetland (CW) as an effective method for domestic wastewater treatment, there is lack of clarity in arriving at well-defined design guidelines. This is particularly due to the fact that the design of CW is dependent on many inter-connected parameters which interact in a complex manner. Consequently, different researchers in the past have tried to address different aspects of this complexity. In this study, an attempt is made to model the influence of relative humidity (RH) in the effectiveness of BOD5 removal. Since it is an accepted fact that plants respond to change in humidity, it is necessary to take this parameter into consideration particularly when the CW is to be designed involving changes in relative humidity over a shorter time horizon (say a couple of months). This study reveals that BOD5out depends on the ratio of BOD5in and relative humidity. An attempt is also made to model the outlet BOD5 using genetic programming with inlet BOD5 and relative humidity as input parameters.

The Relationship Between Apparent Temperature and Daily Number of Live Births in Montreal.

OBJECTIVES: Temperature is a hypothesized determinant of early delivery, but seasonal and long term trends, delayed effects of temperature, and the influence of extreme cold temperatures have not yet been addressed. We aim to study the influence of apparent temperature on daily number of births, considering lag structures, seasonality and long term trends. METHODS: We used daily number of births in conjunction with apparent outdoor temperatures between 1981 and 2010 in Montreal. We used Poisson regression combined with a distributed lag nonlinear model to consider non-linear relationships between temperature and daily number of births across specific lag periods. RESULTS: We found that apparent temperature was associated with the daily number of births in Montreal, with a 1-day delay. We found an increase in births on hot days, and decrease on cold days, both offset by a harvesting effect after 4 and 5 days. CONCLUSIONS FOR PRACTICE: This study suggests that the number of births is affected by extreme temperatures. Obstetric and perinatal service providers should be prepared for spikes in the number of births caused by extreme temperatures.

Searching for the best modeling specification for assessing the effects of temperature and humidity on health: a time series analysis in three European cities.

Epidemiological time series studies suggest daily temperature and humidity are associated with adverse health effects including increased mortality and hospital admissions. However, there is no consensus over which metric or lag best describes the relationships. We investigated which temperature and humidity model specification most adequately predicted mortality in three large European cities. Daily counts of all-cause mortality, minimum, maximum and mean temperature and relative humidity and apparent temperature (a composite measure of ambient and dew point temperature) were assembled for Athens, London, and Rome for 6 years between 1999 and 2005. City-specific Poisson regression models were fitted separately for warm (April-September) and cold (October-March) periods adjusting for seasonality, air pollution, and public holidays. We investigated goodness of model fit for each metric for delayed effects up to 13 days using three model fit criteria: sum of the partial autocorrelation function, AIC, and GCV. No uniformly best index for all cities and seasonal periods was observed. The effects of temperature were uniformly shown to be more prolonged during cold periods and the majority of models suggested separate temperature and humidity variables performed better than apparent temperature in predicting mortality. Our study suggests that the nature of the effects of temperature and humidity on mortality vary between cities for unknown reasons which require further investigation but may relate to city-specific population, socioeconomic, and environmental characteristics. This may have consequences on epidemiological studies and local temperature-related warning systems.

Mortality displacement as a function of heat event strength in 7 US cities.

Mortality rates increase immediately after periods of high air temperature. In the days and weeks after heat events, time series may exhibit mortality displacement-periods of lower than expected mortality. We examined all-cause mortality and meteorological data from 1980 to 2009 in the cities of Atlanta, Georgia; Boston, Massachusetts; Minneapolis-St. Paul, Minnesota; Philadelphia, Pennsylvania; Phoenix, Arizona; Seattle, Washington; and St. Louis, Missouri. We modeled baseline mortality using a generalized additive model. Heat waves were defined as periods of 3 or more consecutive days in which the apparent temperature exceeded a variable percentile. For each heat wave, we calculated the sum of excess and deficit mortality. Mortality displacement, which is the ratio of grand sum deficit to grand sum excess mortality, decreased as a function of event strength in all cities. Displacement was close to 1.00 for the weakest events. At the highest temperatures, displacement varied from 0.35 (95% confidence interval: 0.21, 0.55) to 0.75 (95% confidence interval: 0.54, 0.97). We found strong evidence of acclimatization across cities. Without consideration of displacement effects, the net impacts of heat-wave mortality are likely to be significant overestimations. A statistically significant positive relationship between the onset temperature of nondisplaced heat mortality and mean warm-season temperature (R(2) = 0.78, P < 0.01) suggests that heat mortality thresholds may be predictable across cities.