Long-Term Effect of Temperature Increase on Liver Cancer in Australia: A Bayesian Spatial Analysis.

BACKGROUND: While some evidence has potentially linked climate change to carcinogenic factors, the long-term effect of climate change on liver cancer risk largely remains unclear. OBJECTIVES: Our objective is to evaluate the long-term relationship between temperature increase and liver cancer incidence in Australia. METHODS: We mapped the spatial distribution of liver cancer incidence from 2001 to 2019 in Australia. A Bayesian spatial conditional autoregressive (CAR) model was used to estimate the relationships between the increase in temperature at different lags and liver cancer incidence in Australia, after controlling for chronic hepatitis B prevalence, chronic hepatitis C prevalence, and the Index of Relative Socio-economic Disadvantage. Spatial random effects obtained from the Bayesian CAR model were also mapped. RESULTS: The research showed that the distribution of liver cancer in Australia is spatially clustered, most areas in Northern Territory and Northern Queensland have higher incidence and relative risk. The increase in temperature at the lag of 30 years was found to correlate with the increase in liver cancer incidence in Australia, with a posterior mean of 30.57 [95% Bayesian credible interval (CrI): 0.17, 58.88] for the univariate model and 29.50 (95% CrI: 1.27, 58.95) after controlling for confounders, respectively. The results were not highly credible for other lags. DISCUSSION: Our Bayesian spatial analysis suggested a potential relationship between temperature increase and liver cancer. To our knowledge, this research marks the first attempt to assess the long-term effect of global warming on liver cancer. If the relationship is confirmed by other studies, these findings may inform the development of prevention and mitigation strategies based on climate change projections. https://doi.org/10.1289/EHP14574.

Expert judgement reveals current and emerging UK climate-mortality burden.

Weather and climate patterns play an intrinsic role in societal health, yet a comprehensive synthesis of specific hazard-mortality causes does not currently exist. Country-level health burdens are thus highly uncertain, but harnessing collective expert knowledge can reduce this uncertainty, and help assess diverse mortality causes beyond what is explicitly quantified. Here, surveying 30 experts, we provide the first structured expert judgement of how weather and climate directly impact mortality, using the UK as an example. Current weather-related mortality is dominated by short-term exposure to hot and cold temperatures leading to cardiovascular and respiratory failure. We find additional underappreciated health outcomes, especially related to long-exposure hazards, including heat-related renal disease, cold-related musculoskeletal health, and infectious diseases from compound hazards. We show potential future worsening of cause-specific mortality, including mental health from flooding or heat, and changes in infectious diseases. Ultimately, this work could serve to develop an expert-based understanding of the climate-related health burden in other countries.

Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HE2AT Center study protocol.

INTRODUCTION: African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, compounded by increasing temperatures due to climate change. This study aims to understand the complexities of heat-related health impacts in these cities. The objectives are: (1) mapping intraurban heat risk and exposure using health, socioeconomic, climate and satellite imagery data; (2) creating a stratified heat-health forecast model to predict adverse health outcomes; and (3) establishing an early warning system for timely heatwave alerts. The ultimate goal is to foster climate-resilient African cities, protecting disproportionately affected populations from heat hazards. METHODS AND ANALYSIS: The research will acquire health-related datasets from eligible adult clinical trials or cohort studies conducted in Johannesburg and Abidjan between 2000 and 2022. Additional data will be collected, including socioeconomic, climate datasets and satellite imagery. These resources will aid in mapping heat hazards and quantifying heat-health exposure, the extent of elevated risk and morbidity. Outcomes will be determined using advanced data analysis methods, including statistical evaluation, machine learning and deep learning techniques. ETHICS AND DISSEMINATION: The study has been approved by the Wits Human Research Ethics Committee (reference no: 220606). Data management will follow approved procedures. The results will be disseminated through workshops, community forums, conferences and publications. Data deposition and curation plans will be established in line with ethical and safety considerations.

Multimorbidity and emergency hospitalisations during hot weather.

BACKGROUND: People with chronic diseases are a commonly listed heat-vulnerable group in heat-health action plans. While prior research identifies multiple health conditions that may increase vulnerability to ambient heat, there is minimal evidence regarding the implications of multimorbidity (two or more chronic diseases). METHODS: From the statewide hospital registry of Queensland, Australia, we identified people aged ≥15 years who had emergency hospitalisation(s) between March 2004 and April 2016 and previously had 0, 1, 2, or ≥3 of five chronic diseases: cardiovascular disease, diabetes, mental disorders, asthma/COPD, and chronic kidney disease. We conducted time-stratified case-crossover analyses to estimate the odds ratio of hospitalisations associated with ambient heat exposure in people with different numbers, types, and combinations of chronic diseases. Ambient heat exposure was defined as a 5 °C increase in daily mean temperature above the median. FINDINGS: There were 2,263,427 emergency hospitalisations recorded (48.7% in males and 51.3% in females). When the mean temperature increased, hospitalisation odds increased with chronic disease number, particularly in older persons (≥65 years), males, and non-indigenous people. For instance, in older persons with 0, 1, 2, or ≥3 chronic diseases, the odds ratios associated with ambient heat exposure were 1.00 (95% confidence interval: 0.96, 1.04), 1.06 (1.02, 1.09), 1.08 (1.02, 1.14), and 1.13 (1.07, 1.19), respectively. Among the chronic diseases, chronic kidney disease, and asthma/COPD, either existing alone, together, or in combination with other diseases, were associated with the highest odds of hospitalisations under ambient heat exposure. INTERPRETATION: While individuals with multimorbidity are considered in heat-health action plans, this study suggests the need to consider specifically examining them as a distinct and vulnerable subgroup. FUNDING: Wellcome.

Risk factors associated with heatwave mortality in Chinese adults over 65 years.

Aging populations are susceptible to heat-related mortality because of physiological factors and comorbidities. However, the understanding of individual vulnerabilities in the aging population is incomplete. In the Chinese Longitudinal Healthy Longevity Survey, we assessed daily heatwave exposure individually for 13,527 participants (median age = 89 years) and 3,249 summer mortalities during follow-up from 2008 to 2018. The mortality risk during heatwave days according to relative temperature is approximately doubled (hazard ratio (HR) range = 1.78-1.98). We found that heatwave mortality risks were increased for individuals with functional declines in mobility (HR range = 2.32-3.20), dependency in activities of daily living (HR range = 2.22-3.27), cognitive impairment (HR = 2.22) and social isolation reflected by having nobody to ask for help during difficulties (HR range = 2.14-10.21). Contrary to current understanding, older age was not predictive of heatwave mortality risk after accounting for individual functional declines; no statistical differences were detected according to sex. Beyond age as a risk factor, our findings emphasize that functional aging is an underlying factor in enhancing heatwave resilience. Assessment of functional decline and implementing care strategies are crucial for targeted prevention of mortality during heatwaves.

Exploring interconnections: A comprehensive multi-country analysis of climate change, energy demand, long-term care, and health of older adults.

Challenges faced by many countries are energy insecurity, climate change, and the health and long-term care of growing numbers of older people. These challenges are increasingly intersecting with rising energy prices, aging populations, and an increased frequency and intensity of extreme climate events. This paper gives a deeper understanding of the current and predicted interconnections among these challenges through narrative-driven content and thematic analysis from workshops with a diverse group of international stakeholders from the Global North and Global South. Narratives emerged highlighting a complex nexus of interconnections and presenting critical action areas. Targeted local and global policies and interventions are needed to alleviate stress on health systems, encourage the integrated uptake of clean energy sources, and uphold social justice across all economies. Professionals can use this work to inform the design and implementation of effective interventions and increase the resilience of older adults by better preparing for systemic risks.

Global reductions in manual agricultural work capacity due to climate change.

Manual outdoor work is essential in many agricultural systems. Climate change will make such work more stressful in many regions due to heat exposure. The physical work capacity metric (PWC) is a physiologically based approach that estimates an individual's work capacity relative to an environment without any heat stress. We computed PWC under recent past and potential future climate conditions. Daily values were computed from five earth system models for three emission scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) and three time periods: 1991-2010 (recent past), 2041-2060 (mid-century) and 2081-2100 (end-century). Average daily PWC values were aggregated for the entire year, the growing season, and the warmest 90-day period of the year. Under recent past climate conditions, the growing season PWC was below 0.86 (86% of full work capacity) on half the current global cropland. With end-century/SSP5-8.5 thermal conditions this value was reduced to 0.7, with most affected crop-growing regions in Southeast and South Asia, West and Central Africa, and northern South America. Average growing season PWC could falls below 0.4 in some important food production regions such as the Indo-Gangetic plains in Pakistan and India. End-century PWC reductions were substantially greater than mid-century reductions. This paper assesses two potential adaptions-reducing direct solar radiation impacts with shade or working at night and reducing the need for hard physical labor with increased mechanization. Removing the effect of direct solar radiation impacts improved PWC values by 0.05 to 0.10 in the hottest periods and regions. Adding mechanization to increase horsepower (HP) per hectare to levels similar to those in some higher income countries would require a 22% increase in global HP availability with Sub-Saharan Africa needing the most. There may be scope for shifting to less labor-intensive crops or those with labor peaks in cooler periods or shift work to early morning.

Protocol of an individual participant data meta-analysis to quantify the impact of high ambient temperatures on maternal and child health in Africa (HE2AT IPD).

INTRODUCTION: Globally, recognition is growing of the harmful impacts of high ambient temperatures (heat) on health in pregnant women and children. There remain, however, major evidence gaps on the extent to which heat increases the risks for adverse health outcomes, and how this varies between settings. Evidence gaps are especially large in Africa. We will conduct an individual participant data (IPD) meta-analysis to quantify the impacts of heat on maternal and child health in sub-Saharan Africa. A detailed understanding and quantification of linkages between heat, and maternal and child health is essential for developing solutions to this critical research and policy area. METHODS AND ANALYSIS: We will use IPD from existing, large, longitudinal trial and cohort studies, on pregnant women and children from sub-Saharan Africa. We will systematically identify eligible studies through a mapping review, searching data repositories, and suggestions from experts. IPD will be acquired from data repositories, or through collaboration with data providers. Existing satellite imagery, climate reanalysis data, and station-based weather observations will be used to quantify weather and environmental exposures. IPD will be recoded and harmonised before being linked with climate, environmental, and socioeconomic data by location and time. Adopting a one-stage and two-stage meta-analysis method, analytical models such as time-to-event analysis, generalised additive models, and machine learning approaches will be employed to quantify associations between exposure to heat and adverse maternal and child health outcomes. ETHICS AND DISSEMINATION: The study has been approved by ethics committees. There is minimal risk to study participants. Participant privacy is protected through the anonymisation of data for analysis, secure data transfer and restricted access. Findings will be disseminated through conferences, journal publications, related policy and research fora, and data may be shared in accordance with data sharing policies of the National Institutes of Health. PROSPERO REGISTRATION NUMBER: CRD42022346068.

Lessons from the COVID-19 pandemic: Mortality impacts in Poland versus European Union.

With COVID-19 moving toward an endemic phase, it is worthwhile to identify lessons from the pandemic that can promote the effective strengthening of national health systems. We look at a single country, Poland, and compare it with the European Union (EU) to contrast approaches and outcomes. Among possible relevant indices, we examine characteristics of COVID-19-related mortality and excess all-cause mortality from March 2020 to February 2022. We demonstrate that both the numbers of COVID-related deaths and all-cause deaths in Poland were much higher than the EU average for most months in the study period. We juxtapose the percentage of fully vaccinated population and cumulative COVID-19 deaths per million people for EU Member States and show that typically higher vaccination rates are accompanied by lower mortality. We also show that, in addition to medical science, the use of a risk science toolbox would have been valuable in the management of the COVID-19 pandemic in Poland. Better and more widespread understanding of risk perception of the pandemic and the COVID-19 vaccines would have improved managing vaccine hesitancy, potentially leading to more effective pro-vaccination measures.

A physiological approach for assessing human survivability and liveability to heat in a changing climate.

Most studies projecting human survivability limits to extreme heat with climate change use a 35 °C wet-bulb temperature (Tw) threshold without integrating variations in human physiology. This study applies physiological and biophysical principles for young and older adults, in sun or shade, to improve current estimates of survivability and introduce liveability (maximum safe, sustained activity) under current and future climates. Our physiology-based survival limits show a vast underestimation of risks by the 35 °C Tw model in hot-dry conditions. Updated survivability limits correspond to Tw~25.8-34.1 °C (young) and ~21.9-33.7 °C (old)-0.9-13.1 °C lower than Tw = 35 °C. For older female adults, estimates are ~7.2-13.1 °C lower than 35 °C in dry conditions. Liveability declines with sun exposure and humidity, yet most dramatically with age (2.5-3.0 METs lower for older adults). Reductions in safe activity for younger and older adults between the present and future indicate a stronger impact from aging than warming.

The use of environmental scenarios to project future health effects: a scoping review.

Environmental risks are a substantial factor in the current burden of disease, and their role is likely to increase in the future. Model-based scenario analysis is used extensively in environmental sciences to explore the potential effects of human activities on the environment. In this Review, we examine the literature on scenarios modelling environmental effects on health to identify the most relevant findings, common methods used, and important research gaps. Health outcomes and measures related to climate change (n=106) and air pollution (n=30) were most frequently studied. Studies examining future disease burden due to changes or policies related to dietary risks were much less common (n=10). Only a few studies assessed more than two environmental risks (n=3), even though risks can accumulate and interact with each other. Studies predominantly covered high-income countries and Asia. Sociodemographic, vulnerability, and health-system changes were rarely accounted for; thus, assessing the full effect of future environmental changes in an integrative way is not yet possible. We recommend that future models incorporate a broader set of determinants of health to more adequately capture their effect, as well as the effect of mitigation and adaptation efforts.

A novel climate and health decision support platform: Approach, outputs, and policy considerations.

BACKGROUND: The adverse health impacts of climate change are increasingly apparent and the need for adaptation activities is pressing. Risks, drivers, and decision contexts vary significantly by location, and high-resolution, place-based information is needed to support decision analysis and risk reduction efforts at scale. METHODS: Using the Intergovernmental Panel on Climate Change (IPCC) risk framework, we developed a causal pathway linking heat with a composite outcome of heat-related morbidity and mortality. We used an existing systematic literature review to identify variables for inclusion and the authors' expert judgment to determine variable combinations in a hierarchical model. We parameterized the model for Washington state using observational (1991-2020 and June 2021 extreme heat event) and scenario-driven temperature projections (2036-2065), compared outputs against relevant existing indices, and analyzed sensitivity to model structure and variable parameterization. We used descriptive statistics, maps, visualizations and correlation analyses to present results. RESULTS: The Climate and Health Risk Tool (CHaRT) heat risk model contains 25 primary hazard, exposure, and vulnerability variables and multiple levels of variable combinations. The model estimates population-weighted and unweighted heat health risk for selected periods and displays estimates on an online visualization platform. Population-weighted risk is historically moderate and primarily limited by hazard, increasing significantly during extreme heat events. Unweighted risk is helpful in identifying lower population areas that have high vulnerability and hazard. Model vulnerability correlate well with existing vulnerability and environmental justice indices. DISCUSSION: The tool provides location-specific insights into risk drivers and prioritization of risk reduction interventions including population-specific behavioral interventions and built environment modifications. Insights from causal pathways linking climate-sensitive hazards and adverse health impacts can be used to generate hazard-specific models to support adaptation planning.