• Energy Research

A previous systematic review has shown associations between exposure to high temperatures and negative birth outcomes. To date, a scoping review for heat indices and their use to measure effects of heat on maternal and perinatal health has not been considered.ObjectivesTo provide a scoping review on heat stress and indices for those interested in the epidemiology and working in extreme heat and maternal perinatal health.MethodsThis study is a scoping review based on a previous review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. It identifies the main ways heat stress through different heat indices impacts maternal and perinatal health in available literature. For documents that met the inclusion criteria, we extracted 23 publications.ResultsWe find four heat indices: heat index, apparent temperature, wet bulb globe temperature and universal thermal climate index. Exposure to elevated levels of heat stress can be associated with preterm birth. In addition, the more intense and prolonged duration of exposure to heat stress, the greater the risk of stillbirth. Negative birth outcomes can occur from change in hormonal levels (ie, cortisol), dehydration and blood flow diversion away from the placenta and fetus when suffering from heat stress. All studies demonstrate that certain socioeconomic factors influence the effect of heat on maternal and perinatal health outcomes.ConclusionWe make three suggestions based on the results: (1) heat indices should be standardised across studies and explained. (2) An increased number of perinatal and maternal health outcomes explored. Finally, (3) enhanced collaboration across climate and health to improve understanding.

Introduction: The African continent has been identified as an area of high risk to increasing exposure of heat and has higher levels of social vulnerability. Heat exposure can lead to a rise in certain perinatal and maternal adverse health conditions. We explored the association of heat on seven perinatal and maternal health outcomes. Material and Methods: In this study, data is from Aga Khan University Hospital in Mombasa, Kenya. We evaluated the influence of heat exposure metrics on the outcomes of caesarean sections, low birth weight, low apgar score, preterm birth, stillbirth, assisted vaginal deliveries and long duration of stay in hospital. We carried out pooled time series regression using distributed-lag nonlinear models (lag 0–9 months). Results: We observed an increased odds of caesarean sections with heat exposure at lag 0 indicated by maximum daily Universal Thermal Climate Index (UTCI) between the 50th and the 95th percentile (relative risk 1.21 (1.01,1.46, 95 %CI)) and maximum daily temperature (1.25 (1.03,1.53)). There were increased odds of Low-Birth-Weight Births for lag 0 mean and maximum UTCI. We did not find any significant responses for Wet Bulb Globe Temperature (WBGT). Discussion and Conclusion: Our results show different risk responses for different heat exposure metrics for all perinatal and maternal health outcomes, significantly increasing for low-birth-weight births and caesarean sections. Further research is warranted for Kenya regarding maternal mortality and higher blood loss sometimes associated with caesarean deliveries. In addition, more research is needed on socioeconomics and heat exposure, especially in low– and middle income countries.

Abstract Background In the past decades, climate change has been impacting human lives and health via extreme weather and climate events and alterations in labour capacity, food security, and the prevalence and geographical distribution of infectious diseases across the globe. Climate change and health indicators (CCHIs) are workable tools designed to capture the complex set of interdependent interactions through which climate change is affecting human health. Since 2015, a novel sub-set of CCHIs, focusing on climate change impacts, exposures, and vulnerability indicators (CCIEVIs) has been developed, refined, and integrated by Working Group 1 of the “Lancet Countdown: Tracking Progress on Health and Climate Change”, an international collaboration across disciplines that include climate, geography, epidemiology, occupation health, and economics. Discussion This research in practice article is a reflective narrative documenting how we have developed CCIEVIs as a discrete set of quantifiable indicators that are updated annually to provide the most recent picture of climate change’s impacts on human health. In our experience, the main challenge was to define globally relevant indicators that also have local relevance and as such can support decision making across multiple spatial scales. We found a hazard, exposure, and vulnerability framework to be effective in this regard. We here describe how we used such a framework to define CCIEVIs based on both data availability and the indicators’ relevance to climate change and human health. We also report on how CCIEVIs have been improved and added to, detailing the underlying data and methods, and in doing so provide the defining quality criteria for Lancet Countdown CCIEVIs. Conclusions Our experience shows that CCIEVIs can effectively contribute to a world-wide monitoring system that aims to track, communicate, and harness evidence on climate-induced health impacts towards effective intervention strategies. An ongoing challenge is how to improve CCIEVIs so that the description of the linkages between climate change and human health can become more and more comprehensive.

Abstract Both climate change and rapid urbanization accelerate exposure to heat in the city of Kampala, Uganda. From a network of low-cost temperature and humidity sensors, operational in 2018–2019, we derive the daily mean, minimum and maximum Humidex in order to quantify and explain intra-urban heat stress variation. This temperature-humidity index is shown to be heterogeneously distributed over the city, with a daily mean intra-urban Humidex Index deviation of 1.2 ∘C on average. The largest difference between the coolest and the warmest station occurs between 16:00 and 17:00 local time. Averaged over the whole observation period, this daily maximum difference is 6.4 ∘C between the warmest and coolest stations, and reaches 14.5 ∘C on the most extreme day. This heat stress heterogeneity also translates to the occurrence of extreme heat, shown in other parts of the world to put local populations at risk of great discomfort or health danger. One station in a dense settlement reports a daily maximum Humidex Index of > 40 ∘C in 68% of the observation days, a level which was never reached at the nearby campus of the Makerere University, and only a few times at the city outskirts. Large intra-urban heat stress differences are explained by satellite earth observation products. Normalized Difference Vegetation Index has the highest (75%) power to predict the intra-urban variations in daily mean heat stress, but strong collinearity is found with other variables like impervious surface fraction and population density. Our results have implications for urban planning on the one hand, highlighting the importance of urban greening, and risk management on the other hand, recommending the use of a temperature-humidity index and accounting for large intra-urban heat stress variations and heat-prone districts in urban heat action plans for tropical humid cities.

This study protocol falls within WP2 of HIGH Horizons (assessment of health impacts and facilities), task 2.1 (population-level impacts: measurement). Analyses of heat-health impacts and data science predictive modelling using population-level data from Sweden, Italy (Lazio region), Greece and data from health facilities in Kenya and South Africa (Gauteng province) underpin all other activities in HIGH Horizons. These analyses, along with systematic reviews, will inform testing and selection of global, EU and national indicators. Analyses will also inform cut-off thresholds for an Early Warning System (EWS), whereby a smartphone app (ClimApp-MCH) will deliver personalised warnings and context-specific messages, co-designed locally. The aim of the epidemiological study is to generate evidence to inform the testing and selection of global, EU and national indicators of heat exposure on maternal, neonatal, and child health (MNCH), and to inform cut-off thresholds for a personalised early warning system for pregnant and postpartum women, infants and health workers. The primary objectives of this study are:1) To quantify relationships between ambient temperature exposures and risk of adverse maternal, neonatal, and child health outcomes;2) To identify the relative temperature threshold(s) above which risk of an adverse outcome is increased;3) To determine valid and reliable heat indicators for assessing heat-MNCH impacts at population-level;4) To characterise groups of pregnant women and children at high risk of heat-related conditions;5) To determine if heat-MNCH associations vary by location, climate, facility, or quality of care, as the data allow.Our secondary objectives are:6) To identify critical windows of susceptibility during gestation or during infancy and childhood; 7) To explore impacts of both acute and cumulative heat exposures.

This HIGH Horizons report (deliverable 3.3) presents heat health risk thresholds found in literature, threshold related results from WP2 data analysis, methods of determination of the thresholds, heat stress indices, and recommended thresholds at different heat risk levels of the heat health warning system (HHWS) for pregnant and postpartum women, infants and health workers. The selected cut-off thresholds will be implemented in the personalised early warning system (EWS) that the HIGH Horizons consortium is building for pregnant women, infants and health workers, based on ClimApp. The aim of identifying the heat health risk thresholds is to enable the EWS to use these pre-determined trigger levels of heat stress to alert impending heat health risks and provide advice to pregnant and postpartum women, caregivers of infants and health workers to take actions to reduce health risks.