Heat: a primer for public health researchers.

OBJECTIVES: To provide a primer on the physical characteristics of heat from a biometeorological perspective for those interested in the epidemiology of extreme heat. STUDY DESIGN: A literature search design was used. METHODS: A review of the concepts of heat, heat stress and human heat balance was conducted using Web of Sciences, Scopus and PubMed. RESULTS: Heat, as recognised in the field of human biometeorology, is a complex phenomenon resulting from the synergistic effects of air temperature, humidity and ventilation levels, radiation loads and metabolic activity. Heat should therefore not be conflated with high temperatures. A range of empirical, direct and rational heat stress indices have been developed to assess heat stress. CONCLUSION: The conceptualisation of heat stress is best described with reference to the human heat balance which describes the various avenues for heat gain to and heat loss from the body. Air temperature alone is seldom the reason for heat stress and thus heat-related health effects.

Humidity: A review and primer on atmospheric moisture and human health.

Research examining associations between weather and human health frequently includes the effects of atmospheric humidity. A large number of humidity variables have been developed for numerous purposes, but little guidance is available to health researchers regarding appropriate variable selection. We examine a suite of commonly used humidity variables and summarize both the medical and biometeorological literature on associations between humidity and human health. As an example of the importance of humidity variable selection, we correlate numerous hourly humidity variables to daily respiratory syncytial virus isolates in Singapore from 1992 to 1994. Most water-vapor mass based variables (specific humidity, absolute humidity, mixing ratio, dewpoint temperature, vapor pressure) exhibit comparable correlations. Variables that include a thermal component (relative humidity, dewpoint depression, saturation vapor pressure) exhibit strong diurnality and seasonality. Humidity variable selection must be dictated by the underlying research question. Despite being the most commonly used humidity variable, relative humidity should be used sparingly and avoided in cases when the proximity to saturation is not medically relevant. Care must be taken in averaging certain humidity variables daily or seasonally to avoid statistical biasing associated with variables that are inherently diurnal through their relationship to temperature.

Climate change and heat-related mortality in six cities Part 2: climate model evaluation and projected impacts from changes in the mean and variability of temperature with climate change.

Previous assessments of the impacts of climate change on heat-related mortality use the "delta method" to create temperature projection time series that are applied to temperature-mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heat-related mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature-mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heat-related mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2 degrees C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.

Climate change and heat-related mortality in six cities part 1: model construction and validation.

Heat waves are expected to increase in frequency and magnitude with climate change. The first part of a study to produce projections of the effect of future climate change on heat-related mortality is presented. Separate city-specific empirical statistical models that quantify significant relationships between summer daily maximum temperature (T (max)) and daily heat-related deaths are constructed from historical data for six cities: Boston, Budapest, Dallas, Lisbon, London, and Sydney. 'Threshold temperatures' above which heat-related deaths begin to occur are identified. The results demonstrate significantly lower thresholds in 'cooler' cities exhibiting lower mean summer temperatures than in 'warmer' cities exhibiting higher mean summer temperatures. Analysis of individual 'heat waves' illustrates that a greater proportion of mortality is due to mortality displacement in cities with less sensitive temperature-mortality relationships than in those with more sensitive relationships, and that mortality displacement is no longer a feature more than 12 days after the end of the heat wave. Validation techniques through residual and correlation analyses of modelled and observed values and comparisons with other studies indicate that the observed temperature-mortality relationships are represented well by each of the models. The models can therefore be used with confidence to examine future heat-related deaths under various climate change scenarios for the respective cities (presented in Part 2).

Winter North Atlantic Oscillation, temperature and ischaemic heart disease mortality in three English counties.

As cold weather is an ischaemic heart disease (IHD) risk factor, year-to-year variations of the level of IHD mortality may be partly determined by inter-annual variations in winter climate. This paper investigates whether there is any association between the level of IHD mortality for three English counties and the winter North Atlantic Oscillation (NAO), which exerts a fundamental control on the nature of the winter climate over Western Europe. Correlation and regression analysis was used to explore the nature of the association between IHD mortality and a climate index (CI) that represents the interaction between the NAO and temperature across England for the winters 1974-1975 to 1989-1999. Statistically significant inverse associations between the CI and the level of IHD mortality were found. Generally, high levels of winter IHD mortality are associated with a negative CI, which represents winters with a strong negative phase of the NAO and anomalously low temperatures across England. Moreover, the nature of the CI in the early stages of winter appears to exert a fundamental control on the general level of winter IHD mortality. Because winter climate is able to explain a good proportion of the inter-annual variability of winter mortality, long-lead forecasting of winter IHD mortality appears to be a possibility. The integration of climate-based health forecasts into decision support tools for advanced general winter emergency service and capacity planning could form the basis of an effective adaptive strategy for coping with the health effects of harsh winters.