Future temperature-related mortality in the UK under climate change scenarios: impact of population ageing and bias-corrected climate projections.

BACKGROUND: Exposure to heat and cold poses a serious threat to human health. In the UK, hotter summers, milder winters and an ageing population will shift how populations experience temperature-related health burdens. Estimating future burdens can provide insights on the drivers of temperature-related health effects and removing biases in temperature projections is an essential step to generating these estimates, however, the impact of various methods of correction is not well examined. METHODS: We conducted a detailed health impact assessment by estimating mortality attributable to temperature at a baseline period (2007-2018) and in future decades (2030s, 2050s and 2070s). Epidemiological exposure-response relationships were derived for all England regions and UK countries, to quantify cold and heat risk, and temperature thresholds where mortality increases. UK climate projections 2018 (UKCP18)were bias-corrected using three techniques: correcting for mean bias (shift or SH), variability (bias-correction or BC) and extreme values (quantile mapping or QM). These were applied in the health impact assessment, alongside consideration of population ageing and growth to estimate future temperature-related mortality. FINDINGS: In the absence of adaptation and assuming a high-end emissions scenario (RCP8.5), annual UK temperature-related mortality is projected to increase, with substantial differences in raw vs. calibrated projections for heat-related mortality, but smaller differences for cold-related mortality. The BC approach gave an estimated 29 deaths per 100,000 in the 2070s, compared with 50 per 100,000 using uncorrected future temperatures. We also found population ageing may exert a bigger impact on future mortality totals than the impact from future increases in temperature alone. Estimating future health burdens associated with heat and cold is an important step towards equipping decision-makers to deliver suitable care to the changing population. Correcting inherent biases in temperature projections can improve the accuracy of projected health burdens to support health protection measures and long-term resilience planning.

Ambient heat and acute kidney injury: case-crossover analysis of 1 354 675 automated e-alert episodes linked to high-resolution climate data.

BACKGROUND: As global temperatures continue to rise, the effects of ambient heat on acute kidney injury (AKI) are of growing concern. We used a novel nationwide electronic alert (e-alert) system to detect increases in AKI risk associated with high temperatures. METHODS: We used a case-crossover design to link 1 354 675 AKI episodes occurring in England between April and September in years 2017-2021 to daily maximum temperature data at postcode sector level. AKI episode data were obtained from the UK Renal Registry. There were no further inclusion or exclusion criteria. Conditional logistic regression employing distributed lag non-linear models was used to assess odds of AKI episode on case days compared with day-of-week matched control days. Effects during heatwaves were also assessed using heat-episode analysis. FINDINGS: There were strongly increased odds of AKI episode associated with high temperatures, with odds ratio (OR) 1·623 (95% CI 1·319-1·997) on a day of temperature 32°C compared with one of 17°C, the effects being strongest on a lag of 1 day. There was an OR of 1·020 (1·019-1·020) per 1°C increase in temperature above 17°C. The odds of a heat-related AKI episode were similar between AKI stages 1 and 2, but considerably lower for stage 3 events. A 7-day heatwave in July 2021 was associated with a 28·6% increase in AKI counts (95% CI 26·5-30·7). INTERPRETATION: Heat-related AKI is a growing public health challenge. As even small changes in renal function can affect patient outcomes, susceptible individuals should be advised to take preventive measures whenever hot weather is forecast. Use of an e-alert system allows effects in milder cases that do not require secondary care to also be detected. FUNDING: National Institute for Health and Care Research (NIHR).

Indicators to support local public health to reduce the impacts of heat on health.

Heat exposure presents a significant weather-related health risk in England and Wales, and is associated with acute impacts on mortality and adverse effects on a range of clinical conditions, as well as increased healthcare costs. Most heat-related health outcomes are preventable with health protection measures such as behavioural changes, individual cooling actions, and strategies implemented at the landscape level or related to improved urban infrastructure. We review current limitations in reporting systems and propose ten indicators to monitor changes in heat exposures, vulnerabilities, heat-health outcomes, and progress on adaptation actions. These indicators can primarily inform local area decision-making in managing risks across multiple sectors such as public health, adult and social care, housing, urban planning, and education. The indicators can be used alongside information on other vulnerabilities relevant for heat and health such as underlying morbidity or housing characteristics, to prioritise the most effective adaptation actions for those who need it the most.

The contribution of demographic changes to future heat-related health burdens under climate change scenarios.

Anthropogenic climate change will have a detrimental impact on global health, including the direct impact of higher ambient temperatures. Existing projections of heat-related health outcomes in a changing climate often consider increasing ambient temperatures alone. Population growth and structure has been identified as a key source of uncertainty in future projections. Age acts as a modifier of heat risk, with heat-risk generally increasing in older age-groups. In many countries the population is ageing as lower birth rates and increasing life expectancy alter the population structure. Preparing for an older population, in particular in the context of a warmer climate should therefore be a priority in public health research and policy. We assess the level of inclusion of population growth and demographic changes in research projecting exposure to heat and heat-related health outcomes. To assess the level of inclusion of population changes in the literature, keyword searches of two databases were implemented, followed by reference and citation scans to identify any missed papers. Relevant papers, those including a projection of the heat health burden under climate change, were then checked for inclusion of population scenarios. Where sensitivity to population change was studied the impact of this on projections was extracted. Our analysis suggests that projecting the heat health burden is a growing area of research, however, some areas remain understudied including Africa and the Middle East and morbidity is rarely explored with most studies focusing on mortality. Of the studies pairing projections of population and climate, specifically SSPs and RCPs, many used pairing considered to be unfeasible. We find that not including any projected changes in population or demographics leads to underestimation of health burdens of on average 64 %. Inclusion of population changes increased the heat health burden across all but two studies.

A protocol for analysing the effects on health and greenhouse gas emissions of implemented climate change mitigation actions.

Background: It is crucial to understand the benefits to human health from decarbonisation to galvanise action among decision makers. Most of our existing evidence comes from modelling studies and little is known about the extent to which the health co-benefits of climate change mitigation actions are realised upon implementation. We aim to analyse evidence from mitigation actions that have been implemented across a range of sectors and scales, to identify those that can improve and sustain health, while accelerating progress towards a zero-carbon economy. Objectives: To understand the implementation process of actions and the role of key actors; explain the contextual elements influencing these actions; summarise what effects, both positive and negative, planned and unplanned they may have on emissions of greenhouse gases and health; and to summarise environmental, social, or economic co-benefits. Data: We will review evidence collected through partnership with existing data holders and an open call for evidence. We will also conduct a hand search of reference lists from systematic reviews and websites of organisations relevant to climate change mitigation. Screening: Screening will be done by two reviewers according to a pre-defined inclusion and exclusion criteria. Analysis: We will identify gaps where implementation or evaluation of implementation of mitigation actions is lacking. We will synthesise the findings to describe how actions were implemented and how they achieved results in different contexts, identifying potential barriers and facilitators to their design, implementation, and uptake. We will also synthesise their effect on health outcomes and other co-benefits. Quantitative synthesis will depend on the heterogeneity of outcomes and metrics. Conclusions: Findings will be used to identify lessons that can be learned from successful and unsuccessful mitigation actions, to make inferences on replicability, scalability, and transferability and will contribute to the development of frameworks that can be used by policy makers.

Spatial Variability of Heat-Related Mortality in Barcelona from 1992-2015: A Case Crossover Study Design.

Numerous studies have demonstrated the relationship between summer temperatures and increased heat-related deaths. Epidemiological analyses of the health effects of climate exposures usually rely on observations from the nearest weather station to assess exposure-response associations for geographically diverse populations. Urban climate models provide high-resolution spatial data that may potentially improve exposure estimates, but to date, they have not been extensively applied in epidemiological research. We investigated temperature-mortality relationships in the city of Barcelona, and whether estimates vary among districts. We considered georeferenced individual (natural) mortality data during the summer months (June-September) for the period 1992-2015. We extracted daily summer mean temperatures from a 100-m resolution simulation of the urban climate model (UrbClim). Summer hot days (above percentile 70) and reference (below percentile 30) temperatures were compared by using a conditional logistic regression model in a case crossover study design applied to all districts of Barcelona. Relative Risks (RR), and 95% Confidence Intervals (CI), of all-cause (natural) mortality and summer temperature were calculated for several population subgroups (age, sex and education level by districts). Hot days were associated with an increased risk of death (RR = 1.13; 95% CI = 1.10-1.16) and were significant in all population subgroups compared to the non-hot days. The risk ratio was higher among women (RR = 1.16; 95% CI= 1.12-1.21) and the elderly (RR = 1.18; 95% CI = 1.13-1.22). Individuals with primary education had similar risk (RR = 1.13; 95% CI = 1.08-1.18) than those without education (RR = 1.10; 95% CI= 1.05-1.15). Moreover, 6 out of 10 districts showed statistically significant associations, varying the risk ratio between 1.12 (95% CI = 1.03-1.21) in Sants-Montjuïc and 1.25 (95% CI = 1.14-1.38) in Sant Andreu. Findings identified vulnerable districts and suggested new insights to public health policy makers on how to develop district-specific strategies to reduce risks.

What individual and neighbourhood-level factors increase the risk of heat-related mortality? A case-crossover study of over 185,000 deaths in London using high-resolution climate datasets.

OBJECTIVE: Management of the natural and built environments can help reduce the health impacts of climate change. This is particularly relevant in large cities where urban heat island makes cities warmer than the surrounding areas. We investigate how urban vegetation, housing characteristics and socio-economic factors modify the association between heat exposure and mortality in a large urban area. METHODS: We linked 185,397 death records from the Greater London area during May-Sept 2007-2016 to a high resolution daily temperature dataset. We then applied conditional logistic regression within a case-crossover design to estimate the odds of death from heat exposure by individual (age, sex) and local area factors: land-use type, natural environment (vegetation index, tree cover, domestic garden), built environment (indoor temperature, housing type, lone occupancy) and socio-economic factors (deprivation, English language, level of employment and prevalence of ill-health). RESULTS: Temperatures were higher in neighbourhoods with lower levels of urban vegetation and with higher levels of income deprivation, social-rented housing, and non-native English speakers. Heat-related mortality increased with temperature increase (Odds Ratio (OR), 95% CI = 1.039, 1.036-1.043 per 1 °C temperature increase). Vegetation cover showed the greatest modification effect, for example the odds of heat-related mortality in quartiles with the highest and lowest tree cover were OR, 95%CI 1.033, 1.026-1.039 and 1.043, 1.037-1.050 respectively. None of the socio-economic variables were a significant modifier of heat-related mortality. CONCLUSIONS: We demonstrate that urban vegetation can modify the mortality risk associated with heat exposure. These findings make an important contribution towards informing city-level climate change adaptation and mitigation policies.

Geographical access to GPs and modes of cancer diagnosis in England: a cross-sectional study.

BACKGROUND: Poor geographical access to health services and routes to a cancer diagnosis such as emergency presentations have previously been associated with worse cancer outcomes. However, the extent to which access to GPs determines the route that patients take to obtain a cancer diagnosis is unknown. METHODS: We used a linked dataset of cancer registry and hospital records of patients with a cancer diagnosis between 2006 and 2010 across eight different cancer sites. Primary outcomes were defined as 'desirable routes to diagnosis' [screen-detected and 2-week wait (TWW) referrals] and 'less desirable routes' [emergency presentations and death certificate only (DCO)]. All other routes (GP referral, inpatient elective and other outpatient) were specified as the reference category. Geographical access was measured as travel time in minutes from patients to their GP, and multinomial logistic regression was used to estimate relative risk ratios (RRR). RESULTS: Longer travel was associated with increased risk of diagnosis via emergency and DCO, but decreased risk of diagnosis via screening and TWW. Patients travelling over 30 minutes had the highest risk of a DCO diagnosis, which was statistically significant for breast, colorectal, lung, prostate, stomach and ovarian cancers (compared with patients with travel times ≤10 minutes: RRR 5.89, 7.02, 2.30, 4.75, 10.41; P < 0.01 and 3.51, P < 0.05). DISCUSSION: Poor access to GPs may discourage early engagement with health services, decreasing the likelihood of screening uptake and increasing the likelihood of emergency presentations. Extra effort is needed to promote early diagnosis in more distant patients.

Variation in Cold-Related Mortality in England Since the Introduction of the Cold Weather Plan: Which Areas Have the Greatest Unmet Needs?

: The Cold Weather Plan (CWP) in England was introduced to prevent the adverse health effects of cold weather; however, its impact is currently unknown. This study characterizes cold-related mortality and fuel poverty at STP (Sustainability and Transformation Partnership) level, and assesses changes in cold risk since the introduction of the CWP. Time series regression was used to estimate mortality risk for up to 28 days following exposure. Area level fuel poverty was used to indicate mitigation against cold exposure and mapped alongside area level risk. We found STP variations in mortality risk, ranging from 1.74, 1.44⁻2.09 (relative risk (RR), 95% CI) in Somerset, to 1.19, 1.01⁻1.40 in Cambridge and Peterborough. Following the introduction of the CWP, national-level mortality risk declined significantly in those aged 0⁻64 (1.34, 1.23⁻1.45, to 1.09, 1.00⁻1.19), but increased significantly among those aged 75+ (1.36, 1.28⁻1.44, to 1.58, 1.47⁻1.70) and for respiratory conditions (1.78, 1.56⁻2.02, to 2.4, 2.10⁻2.79). We show how spatial variation in cold mortality risk has increased since the introduction of the CWP, which may reflect differences in implementation of the plan. Combining risk with fuel poverty information identifies 14 STPs with the greatest need to address the cold effect, and that would gain most from enhanced CWP activity or additional intervention measures.

Impact of travel time and rurality on presentation and outcomes of symptomatic colorectal cancer: a cross-sectional cohort study in primary care.

BACKGROUND: Several studies have reported a survival disadvantage for rural dwellers who develop colorectal cancer, but the underlying mechanisms remain obscure. Delayed presentation to GPs may be a contributory factor, but evidence is lacking. AIM: To examine the association between rurality and travel time on diagnosis and survival of colorectal cancer in a cohort from northeast Scotland. DESIGN AND SETTING: The authors used a database linking GP records to routine data for patients diagnosed between 1997 and 1998, and followed up to 2011. METHOD: Primary outcomes were alarm symptoms, emergency admissions, stage, and survival. Travel time in minutes from patients to GP was estimated. Logistic and Cox regression were used to model outcomes. Interaction terms were used to determine if travelling time impacted differently on urban versus rural patients. RESULTS: Rural patients and patients travelling farther to the GP had better 3-year survival. When the travel outcome associations were explored using interaction terms, the associations differed between rural and urban areas. Longer travel in urban areas significantly reduced the odds of emergency admissions (odds ratio [OR] 0.62, P<0.05), and increased survival (hazard ratio 0.75, P<0.05). Longer travel also increased the odds of presenting with alarm symptoms in urban areas; this was nearly significant (OR 1.34, P = 0.06). Presence of alarm symptoms reduced the likelihood of emergency admissions (OR 0.36, P<0.01). CONCLUSION: Living in a rural area, and travelling farther to a GP in urban areas, may reduce the likelihood of emergency admissions and poor survival. This may be related to how patients present with alarm symptoms.

Effect of night-time temperatures on cause and age-specific mortality in London.

BACKGROUND: High ambient temperatures are associated with an acute increase in mortality risk. Although heat exposure during the night is anecdotally cited as being important, this has not been rigorously demonstrated in the epidemiological literature. METHODS: We quantified the contribution of nighttime temperatures using time-series quasi-Poisson regression on cause and age-specific daily mortality in London between 1993 and 2015. Daytime and nighttime exposures were characterized by average temperatures between 9 am and 9 pm and between 4 am and 8 am, respectively, lagged by 7 days. We also examined the differential impacts of hot and cool nights preceded by very hot days. All models were adjusted for air quality, season, and day of the week. Nighttime models were additionally adjusted for daytime exposure. RESULTS: Effects from nighttime exposure persisted after adjusting for daytime exposure. This was highest for stroke, RR (relative risk) = 1.65 (95% confidence interval (CI) = 1.27 to 2.14) estimated by comparing mortality risk at the 80th and 99th temperature percentiles. Compared to daytime exposure, nighttime exposure had a higher mortality risk on chronic ischemic and stroke and in the younger age groups. Respiratory mortality was most sensitive to daytime temperatures. Hot days followed by hot nights had a greater mortality risk than hot days followed by cool nights. CONCLUSIONS: Nighttime exposures make an additional important contribution to heat-related mortality. This impact was highest on warm nights that were preceded by a hot day, which justifies the alert criteria in heat-health warning system that is based on hot days followed by hot nights. The highest mortality risk was from stroke; targeted interventions would benefit patients most susceptible to stroke.

Geographical disparities in access to cancer management and treatment services in England.

This study seeks to examine the extent to which cancer services are geographically located according to cancer incidence, and assess the association with cancer survival. We identified hospital sites serving English PCTs (Primary Care Trusts) with the management and treatment of breast, lung and colorectal cancer. Geographical access was estimated as travel time in minutes from LSOAs (Lower Super Output Areas) to the nearest hospital site and aggregated to PCT level. Correlations between PCT level mean travel times and cancer cases were estimated using Spearman's rank correlation. Associations between PCT level mean travel times and cancer relative survival rates were estimated using linear regression with adjustment for area deprivation and for a PCT level measure of the reported ease of obtaining a doctor's appointment. We found that cancer services tended to be located farther from areas with more cancer cases, and longer average travel times are associated with worse survival after adjustment for age, sex, year and area deprivation. This suggests that geographical access to cancer services remains a concern in England.