The study’s design is a textbook example of modern environmental epidemiology. The team drew on the Ministry of Health Mortality Collection within Stats NZ’s Integrated Data Infrastructure, capturing every registered death in the country from 1 January 1999 to 30 April 2025. Each death was matched to daily heat exposure in the person’s Territorial Authority of residence, reconstructed from weather-station observations in the National Climate Database maintained by the National Institute of Water and Atmospheric Research. To estimate the acute effect of heat, the researchers used a time-stratified case-crossover design, a self-matched method in which each person’s exposure on the day of death is compared with exposure on nearby referent days falling on the same weekday within the same calendar month. Because every individual serves as their own control, time-invariant personal characteristics, seasonality, long-term trends and day-of-week effects are absorbed by the design itself, leaving a clean estimate of the short-term heat-mortality association.

What distinguishes this study from most of its predecessors is the choice of exposure metric. Alongside conventional air-temperature summaries, the team computed the wet-bulb globe temperature, or WBGT, a composite heat-stress index that integrates air temperature with humidity, radiation and wind speed. Developed in the 1950s to prevent heat illness among US military recruits and later codified in occupational health standards such as ISO 7243, WBGT captures the combined thermal load on the human body far better than a thermometer reading alone. The researchers applied the Liljegren physical model to translate standard meteorological measurements into daily WBGT indices based on mean, maximum and minimum temperatures, creating three parallel exposure measures for every district and day. Missing radiation and wind inputs in a small fraction of district-days were filled using multiple imputation by chained equations, a statistically rigorous approach that draws on contemporaneous and recent meteorological information.

The headline results are striking in their consistency. In the all-cause, full-year sample, the odds of death rose by 0.44 percent for every 1 degree Celsius increase in WBGT based on mean daily temperature, and by 0.39 percent per degree of mean air temperature. Restricting the analysis to the warm season, from October to March, sharpened the associations to 0.57 percent and 0.51 percent respectively. Mean-based measures outperformed maximum- and minimum-based measures within both metric families, suggesting that sustained daily heat load, rather than brief afternoon peaks, is what matters most for short-term mortality. When the team compared models statistically, WBGT-only models fit better than temperature-only models, with lower Akaike information criterion values and significant likelihood-ratio improvements, indicating that humidity, radiation and wind carry genuine additional information about lethal heat beyond what a thermometer can see.

To translate these odds ratios into human terms, the researchers performed a simple scaling exercise. A uniform 1 degree Celsius increase in mean WBGT across the country would correspond to roughly 140 additional all-cause deaths per year under full-year assumptions, and about 110 additional non-injury deaths. Restricted to the warm season alone, the same shift implies approximately 85 excess all-cause deaths annually. These are illustrative figures that abstract from spatially differentiated warming and behavioural adaptation, but they give policymakers a tangible benchmark: in a nation of about five million people, even a single degree of additional heat stress claims a measurable annual toll.

The heterogeneity analyses reveal where the burden falls. When Territorial Authorities were grouped by their mean warm-season WBGT into cool, moderate and hot climate tertiles, the per-degree odds increase climbed monotonically from 0.17 percent in the coolest districts to 0.43 percent in moderate ones and 0.67 percent in the hottest. This gradient is consistent with an emerging international pattern in which populations in historically cooler regions may be less adapted, yet the strongest associations here appeared in the warmest districts, hinting that sustained exposure compounds risk. Women showed consistently higher point estimates than men, with a 0.53 percent odds increase per degree of WBGT-Tmean compared with 0.34 percent for men, and the clearest age-specific signal emerged among adults aged 60 and over, where women again faced higher estimates than men. These findings align with physiological expectations that reduced thermoregulatory reserve in older adults heightens vulnerability, and they carry direct implications for aged-care planning and community health services.

Beyond the same-day estimates, the team deployed distributed lag non-linear models to trace how heat effects unfold over the following week. The cumulative exposure-response curves were broadly U-shaped, with fitted minima around 11 to 12 degrees Celsius in the full-year models and rising cumulative odds on the warm side, most clearly supported across the upper-middle of the exposure range. The warm-season curves shifted rightward and became right-skewed, but the qualitative pattern held across metrics, lag windows of 0 to 3, 0 to 7 and 0 to 14 days, and alternative bin thresholds. Robustness checks, including a symmetric 28-day referent window, shifted bin cut points, calendar-period splits and the exclusion of districts with imputed meteorological inputs, all left the main conclusions intact, a testament to the care invested in the empirical design.

The study arrives amid unmistakable evidence that New Zealand’s climate is changing. The country’s seven-station temperature series records a 0.91 degree Celsius rise over the twentieth century, 2024 was the nation’s tenth-warmest year on record, and government projections anticipate that hot days above 25 degrees Celsius could become two to four times more frequent by 2090. The unprecedented 2017-18 austral summer heatwave, with land temperature anomalies of about 2.2 degrees Celsius and sea-surface anomalies reaching 3.7 degrees Celsius in the eastern Tasman Sea, offered a preview of this future. Previous New Zealand evidence had been fragmentary: a Christchurch time-series study from 2000, a Canterbury heatwave pilot, and an expert assessment estimating roughly 14 heat-related deaths per year among older adults in Auckland and Christchurch. The new national analysis replaces these fragments with a coherent, powered, individual-level picture.

The limitations are candidly acknowledged. Exposure was assigned at the district-day level, smoothing over within-district variation that matters in topographically diverse and coastal areas, and the WBGT indices were built from daily summaries rather than hourly data, potentially blurring the timing of peak heat stress. Non-differential exposure error of this kind most likely attenuates rather than inflates the estimated associations, meaning the true burden could be larger. Cause-of-death coding was available only through 2020 for the non-injury analyses, and the case-crossover design, centred on deaths, cannot yet model non-fatal outcomes. The authors flag an individual-day population panel as the next step. Even so, the core message stands firm: measurable heat-mortality associations exist in a temperate maritime climate, they are stronger in the warm season, sharpest among older adults and women, and steepest in the hottest districts. As New Zealand’s climate continues to warm, heat-health warning systems, seasonal preparedness and locally calibrated thresholds will no longer be optional extras but essential infrastructure.

Subject of Research: The association between short-term heat exposure, measured by wet-bulb globe temperature and air temperature, and mortality in Aotearoa New Zealand.

Article Title: Heat exposure and mortality in Aotearoa New Zealand: a time-stratified case-crossover study

Article References: Lu, S., Noy, I., & Stone, D. (2026). Heat exposure and mortality in Aotearoa New Zealand: a time-stratified case-crossover study. Regional Environmental Change, 26(3), Article 184. https://doi.org/10.1007/s10113-026-02667-y

Image Credits: AI Generated

DOI: 10.1007/s10113-026-02667-y

Keywords: heat exposure, mortality, wet-bulb globe temperature, New Zealand, case-crossover study, climate change, heat stress, public health, distributed lag non-linear models, warm season, older adults, temperature

The study, led by environmental epidemiologist Amruta Nori-Sarma of Harvard T.H. Chan School of Public Health in collaboration with colleagues at Truveta, Harvard, and Boston University, exploited a technological capability that earlier generations of heat researchers lacked: continuously refreshed electronic health record data. Rather than waiting months for claims data to be processed and aggregated, the team drew on state-day counts of emergency department visits from 19 eastern states, allowing them to quantify the health burden of the summer 2025 heatwaves while the season was still underway. In total, the analysis encompassed 8,169,637 emergency department visits recorded during the warm seasons of 2023 through 2025, providing a robust historical baseline against which the 2025 episodes could be compared.

The two heatwaves under scrutiny were stark in their timing and severity. The first gripped the region from 22 to 25 June 2025, and the second returned from 10 to 13 August 2025, engulfing the eastern United States in conditions that triggered National Weather Service heat alerts across much of the study area. To estimate how many visits these episodes caused, the researchers compared observed visit counts during the heatwave windows with counterfactual predictions of what visits would have been under typical temperature conditions, using temperature-health associations estimated from the prior three warm seasons.

Technically, the analysis rested on a conditional Poisson model, a statistical framework well suited to time-series data on disease counts. The researchers stratified time by year, calendar month, and day of week, with stratum-specific fixed effects that absorb routine patterns in healthcare utilization, such as weekday and seasonal variation. This design effectively compares hot days with cooler days occurring under otherwise similar conditions, a strategy closely related to the time-stratified case-crossover approach widely used in environmental epidemiology. Temperature exposure was modeled using distributed lag non-linear models, or DLNMs, which capture two crucial features of heat’s health effects simultaneously: the non-linear dose-response relationship between temperature and risk, and the fact that effects unfold over multiple days, with heat stress on one day influencing emergency visits over a window of zero to four days afterward.

The headline numbers were striking. During the June 2025 heatwave, the researchers estimated that 9.2 percent of all-cause emergency department visits were attributable to heat over the zero-to-four-day lag window, with a 95 percent confidence interval of 6.2 to 11.6 percent. During the August heatwave, the attributable fraction was 8.3 percent, with a confidence interval of 6.0 to 10.1 percent. In plain terms, roughly one in every eleven or twelve people who walked into an emergency department in these nineteen states during those weeks was there, at least in part, because of extreme heat. Similar patterns emerged when the team examined cumulative lags and cause-specific outcomes, indicating that the association was not an artifact of a single modeling choice.

Because the underlying data included diagnostic information, the researchers could decompose the burden by cause. Beyond direct heat-related illness diagnoses, they tracked emergency visits for kidney disease and for mental health conditions, both of which have well-documented physiological links to heat exposure. Kidney disease is acutely sensitive to dehydration and thermal strain, while a growing body of literature connects high ambient temperatures to psychiatric crises, including exacerbations of mood disorders and substance-related emergencies. The lag-specific analyses showed that the association between the 99th percentile of daily maximum temperature, about 36.9 degrees Celsius, and the sample median of 27 degrees Celsius was strongest on the same day for direct heat illness, while kidney and mental health outcomes followed somewhat different lag structures, consistent with the diverse physiological pathways through which heat injures the human body.

Those pathways are worth spelling out. Extreme heat forces the cardiovascular system to work harder, shunting blood toward the skin to dissipate warmth and increasing cardiac output, changes that laboratory studies involving more than 400 controlled heat exposure experiments have documented in detail. In people with preexisting heart disease, this added strain can precipitate decompensation. Dehydration concentrates the blood and promotes the formation of kidney stones and acute kidney injury, particularly in older adults and in people taking common medications that impair thermoregulation or fluid balance. Meanwhile, heat disrupts sleep, alters neurotransmitter function, and can increase impulsivity and aggression, mechanisms that plausibly underlie the observed rise in mental health emergency visits during hot weather.

The heterogeneity analyses added an important dimension to the findings. By fitting subgroup models for six age groups, three US census regions, and both sexes, the researchers probed whether the temperature-emergency visit association varied across populations. The results, visualized in forest plots comparing rate ratios at lag zero, showed differences by age, region, and sex, echoing decades of evidence that the very young, older adults, and residents of areas unaccustomed to extreme heat bear disproportionate risk. The state-specific exposure-response functions also revealed geographic variation: states with historically milder summers tended to show steeper increases in emergency visits per degree of warming, a pattern consistent with the idea that populations adapt, physiologically and infrastructurally, to the temperatures they usually experience, and that anomalous heat is most damaging where it is least familiar.

Methodological sensitivity checks strengthened the study’s credibility. The team replicated the primary analysis using daily average temperature instead of daily maximum temperature, and separately extended the lag window from four to seven days; both variations reproduced the central findings. Exposure data were drawn from the Open-Meteo weather API and National Weather Service records, and heat alert dates by state were compiled from National Weather Service advisories, allowing the investigators to anchor their heatwave definitions in the same official warnings that reached the public during those weeks. All analytic code, including the data extraction scripts, DLNM fitting routines, meta-analysis, and attributable burden estimation, has been made publicly available on GitHub, an unusual and welcome degree of transparency for a rapidly produced surveillance analysis.

The broader significance of the study lies less in any single percentage than in what it demonstrates about the future of climate-health surveillance. Traditional epidemiology delivers its verdicts long after the disaster has passed, when the findings can inform the next heat season but not the current one. By contrast, a near-real-time pipeline built on continuously refreshed electronic health records can tell public health officials, while a heatwave is still unfolding, how many excess patients are arriving, which conditions are driving the surge, and where resources are most strained. The authors argue that this capability should become a standing component of heat preparedness, complementing heat action plans and warning systems whose effectiveness, demonstrated in cities from Philadelphia to Montreal, depends on knowing when and where the danger peaks. As climate change renders summers like 2025 more frequent and more intense, the study suggests that the emergency department itself, properly instrumented, can serve as an early-warning sensor for the health impacts of a warming world, and that the true toll of extreme heat is far larger than the narrow category of heatstroke diagnoses would suggest. Nearly a tenth of all emergency care during those scorching weeks was heat’s shadow, and counting it in real time may be the first step toward preventing it.

Subject of Research: Attribution of summer 2025 US heatwave emergency department visits using electronic health records

Article Title: Impact of the summer 2025 heatwaves on emergency department visits in the USA

Article References: Nori-Sarma, A., Cartwright, B. M., Zanobetti, A., Pastwa, A., Stucky, N., & Willis, M. D. (2026). Impact of the summer 2025 heatwaves on emergency department visits in the USA. Nature Health. https://doi.org/10.1038/s44360-026-00194-y

Image Credits: AI Generated

DOI: 10.1038/s44360-026-00194-y

Keywords: heatwaves, emergency department visits, electronic health records, extreme heat, public health surveillance, climate change, epidemiology, distributed lag non-linear models, heat-related illness, kidney disease, mental health, United States