Daily average temperature and mortality among the elderly : a meta-analysis and systematic review of epidemiological evidence

The impact of climate change on the health of vulnerable groups such as the elderly has been of increasing concern. However, to date there has been no meta-analysis of current literature relating to the effects of temperature fluctuations upon mortality amongst the elderly. We synthesised risk estimates of the overall impact of daily mean temperature on elderly mortality across different continents. A comprehensive literature search was conducted using MEDLINE and PubMed to identify papers published up to December 2010. Selection criteria including suitable temperature indicators, endpoints, study-designs and identification of threshold were used. A two-stage Bayesian hierarchical model was performed to summarise the percent increase in mortality with a 1°C temperature increase (or decrease) with 95% confidence intervals in hot (or cold) days, with lagged effects also measured. Fifteen studies met the eligibility criteria and almost 13 million elderly deaths were included in this meta-analysis. In total, there was a 2-5% increase for a 1°C increment during hot temperature intervals, and a 1-2 % increase in all-cause mortality for a 1°C decrease during cold temperature intervals. Lags of up to 9 days in exposure to cold temperature intervals were substantially associated with all-cause mortality, but no substantial lagged effects were observed for hot intervals. Thus, both hot and cold temperatures substantially increased mortality among the elderly, but the magnitude of heat-related effects seemed to be larger than that of cold effects within a global context.

Seasonal variation in month of diagnosis in children with type 1 diabetes registered in 23 European centers during 1989-2008: little short-term influence of sunshine hours or average temperature

BACKGROUND: The month of diagnosis in childhood type 1 diabetes shows seasonal variation.

OBJECTIVE: We describe the pattern and investigate if year-to-year irregularities are associated with meteorological factors using data from 50 000 children diagnosed under the age of 15 yr in 23 population-based European registries during 1989-2008.

METHODS: Tests for seasonal variation in monthly counts aggregated over the 20 yr period were performed. Time series regression was used to investigate if sunshine hour and average temperature data were predictive of the 240 monthly diagnosis counts after taking account of seasonality and long term trends.

RESULTS: Significant sinusoidal pattern was evident in all but two small centers with peaks in November to February and relative amplitudes ranging from ±11 to ±38% (median ±17%). However, most centers showed significant departures from a sinusoidal pattern. Pooling results over centers, there was significant seasonal variation in each age-group at diagnosis, with least seasonal variation in those under 5 yr. Boys showed greater seasonal variation than girls, particularly those aged 10-14 yr. There were no differences in seasonal pattern between four 5-yr sub-periods. Departures from the sinusoidal trend in monthly diagnoses in the period were significantly associated with deviations from the norm in average temperature (0.8% reduction in diagnoses per 1 °C excess) but not with sunshine hours.

CONCLUSIONS: Seasonality was consistently apparent throughout the period in all age-groups and both sexes, but girls and the under 5 s showed less marked variation. Neither sunshine hour nor average temperature data contributed in any substantial way to explaining departures from the sinusoidal pattern.

Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

Spatiotemporal model or time series model for assessing city-wide temperature effects on mortality?

Most studies examining the temperature–mortality association in a city used temperatures from one site or the average from a network of sites. This may cause measurement error as temperature varies across a city due to effects such as urban heat islands. We examined whether spatiotemporal models using spatially resolved temperatures produced different associations between temperature and mortality compared with time series models that used non-spatial temperatures. We obtained daily mortality data in 163 areas across Brisbane city, Australia from 2000 to 2004. We used ordinary kriging to interpolate spatial temperature variation across the city based on 19 monitoring sites. We used a spatiotemporal model to examine the impact of spatially resolved temperatures on mortality. Also, we used a time series model to examine non-spatial temperatures using a single site and the average temperature from three sites. We used squared Pearson scaled residuals to compare model fit. We found that kriged temperatures were consistent with observed temperatures. Spatiotemporal models using kriged temperature data yielded slightly better model fit than time series models using a single site or the average of three sites' data. Despite this better fit, spatiotemporal and time series models produced similar associations between temperature and mortality. In conclusion, time series models using non-spatial temperatures were equally good at estimating the city-wide association between temperature and mortality as spatiotemporal models.

High-precision diode-laser-based temperature measurement for air refractive index compensation

We present a laser-based system to measure the refractive index of air over a long path length. In optical distance measurements it is essential to know the refractive index of air with high accuracy. Commonly, the refractive index of air is calculated from the properties of the ambient air using either Ciddor or Edlén equations, where the dominant uncertainty component is in most cases the air temperature. The method developed in this work utilises direct absorption spectroscopy of oxygen to measure the average temperature of air and of water vapor to measure relative humidity. The method allows measurement of temperature and humidity over the same beam path as in optical distance measurement, providing spatially well matching data. Indoor and outdoor measurements demonstrate the effectiveness of the method. In particular, we demonstrate an effective compensation of the refractive index of air in an interferometric length measurement at a time-variant and spatially non-homogenous temperature over a long time period. Further, we were able to demonstrate 7 mK RMS noise over a 67 m path length using 120 s sample time. To our knowledge, this is the best temperature precision reported for a spectroscopic temperature measurement.

Effects of temperature on CO2 exchange between the atmosphere and an alpine meadow

The alpine meadow ecosystem on the Qinghai-Tibetan Plateau is characterized by low temperatures because of its high elevation. The low-temperature environment may limit both ecosystem photosynthetic CO2 uptake and ecosystem respiration, and thus affect the net ecosystem CO2 exchange (NEE). We clarified the low-temperature constraint on photosynthesis and respiration in an alpine meadow ecosystem on the northern edge of the plateau using flux measurements obtained by the eddy covariance technique in two growing seasons. When we compared NEE during the two periods, during which the leaf area index and other environmental parameters were similar but the mean temperature differed, we found that NEE from 9 August to 10 September 2001, when the average temperature was low, was greater than that during the same period in 2002, when the average temperature was high, but the ecosystem gross primary production was similar during the two periods. Further analysis showed that ecosystem respiration was significantly higher in 2002 than in 2001 during the study period, as estimated from the relationship between temperature and nighttime ecosystem respiration. The results suggest that low temperature controlled the NEE mainly through its influence on ecosystem respiration. The annual NEE, estimated from 15 January 2002 to 14 January 2003, was about 290 g CO2 m(-2) year(-1). The optimum temperature for ecosystem NEE under light-saturated conditions was estimated to be around 15 degrees C.

Mapping stone surface temperature fluctuations: Implications for lichen distribution and biomodification on historic stone surfaces

The exposure of historic stone to processes of lichen-induced surface biomodification is determined, first and foremost, by the bioreceptivity of those surfaces to lichen colonization. As an important component of surface bioreceptivity, spatiotemporal variation in stone surface temperature plays a critical role in the spatial distribution of saxicolous lichen on historic stone structures, especially within seasonally hot environments. The ornate limestone and tufa stairwell of the Monastery of Cartuja (1516), Granada, Spain, exhibits significant aspect-related differences in lichen distribution. Lichen coverage and
diurnal fluctuations in stone surface temperature on the stairwell were monitored and mapped, under anticyclonic conditions in summer and winter, using an infrared thermometer and Geographical Information Systems approach. This research suggests that it is not extreme high surface temperatures that
determine the presence or absence of lichen coverage on stonework. Instead, average stone surface temperatures
over the course of the year seem to play a critical role in determining whether or not surfaces are receptive to lichen colonization and subsequent biomodification. It is inferred that lichen, capable of surviving extreme surface temperatures during the Mediterranean summer in an ametabolic state, require a respite period of lower temperatures within which they can metabolize, grow and reproduce.
The higher the average annual temperature a surface experiences, the shorter the respite period for any lichen potentially inhabiting that surface. A critical average temperature threshold of approximately 21 ?C has been identified on the stairwell, with average stone surface temperatures greater than this
generally inhibiting lichen colonization. A brief visual condition assessment between lichen-covered and lichen-free surfaces on the limestone sections of the stairwell suggests relative bioprotection induced by lichen coverage, with stonework quality and sharpness remaining more defined beneath lichen-covered surfaces. The methodology employed in this paper may have further applications in the monitoring and mapping of thermal stress fatigue on historic building materials.

Persistent unequal sex ratio in a population of grayling (salmonidae) and possible role of temperature increase.

In some fishes, water chemistry or temperature affects sex determination or creates sex-specific selection pressures. The resulting population sex ratios are hard to predict from laboratory studies if the environmental triggers interact with other factors, whereas in field studies, singular observations of unusual sex ratios may be particularly prone to selective reporting. Long-term monitoring largely avoids these problems. We studied a population of grayling (Thymallus thymallus) in Lake Thun, Switzerland, that has been monitored since 1948. Samples of spawning fish have been caught about 3 times/week around spawning season, and water temperature at the spawning site has been continuously recorded since 1970. We used scale samples collected in different years to determine the average age of spawners (for life-stage specific analyses) and to identify the cohort born in 2003 (an extraordinarily warm year). Recent tissue samples were genotyped on microsatellite markers to test for genetic bottlenecks in the past and to estimate the genetically effective population size (N(e) ). Operational sex ratios changed from approximately 65% males before 1993 to approximately 85% males from 1993 to 2011. Sex ratios correlated with the water temperatures the fish experienced in their first year of life. Sex ratios were best explained by the average temperature juvenile fish experienced during their first summer. Grayling abundance is declining, but we found no evidence of a strong genetic bottleneck that would explain the apparent lack of evolutionary response to the unequal sex ratio. Results of other studies show no evidence of endocrine disruptors in the study area. Our findings suggest temperature affects population sex ratio and thereby contributes to population decline. Persistencia de Proporción de Sexos Desigual en una Población de Tímalos (Salmonidae) y el Posible Papel del Incremento de la Temperatura.

The optimum temperature for long-season cropping in the everbearing strawberry 'Everest'

The prolonged season of everbearing strawberries causes vegetative growth and fruiting to coincide, so the influence of the environment on the balance of assimilate partitioning between vegetative and reproductive growth is important for optimised long-season production. Fruiting patterns were evaluated over three seasons for the everbearing strawberry 'Everest'. A range of temperatures (15-27 degrees C) was studied in the first season to establish a temperature response curve. Detailed transfer treatments in the second and third seasons gave insight into heat-induced cropping troughs ('thermo-dormancy'). The detrimental effect on yield of thermo-dormancy was prevented by cool night-time temperature during the periods of heat stress, a treatment that resulted in the largest total fruit fresh weight and overall yield. The highest yields were recorded for plants grown between 18 and 23 degrees C. At higher temperatures fruit number increased, but fruit weight decreased. The importance of night-time temperature in optimising long-season fruit production has significance for commercial production, in which protected cropping tends to increase average temperature through the season.

Analysis of shade and temperature effects on assimilate partitioning in the everbearing strawberry 'Everest' as the basis for optimised long-season fruit production

Growth patterns and cropping were evaluated over the season for the everbearing strawberry 'Everest' at a range of temperatures (15-27degreesC) in two light environments (ambient and 50% shade). The highest yield was recorded for unshaded plants grown at 23degreesC, but the optimum temperature for vegetative growth was 15degreesC. With increasing temperature fruit number increased, but fruit weight decreased. Fruit weight was also significantly reduced by shade, and although 'Everest' showed a degree of shade tolerance in vegetative growth, yield was consistently reduced by shade. Shade also reduced the number of crowns developed by the plants over the course of the season, emphasising that crown number was ultimately the limiting factor for yield potential. We conclude that, in contrast to Junebearers which partition more assimilates to fruit at temperatures around 15degreesC (Le Miere et al., 1998), optimised cropping in the everbearer 'Everest' is achieved at the significantly higher temperature of 23degreesC. These findings have significance for commercial production, in which protection tends to reduce light levels but increase average temperature throughout the season.

Pulpal temperature increases with Er : YAG laser and high-speed handpieces

Statement of problem. During tooth preparation, both high-speed handpieces and lasers generate heat, which, if not controlled, can cause pulpal necrosis.Purpose. The aim of this study was to compare temperature increases produced by a high-speed dental handpiece with those produced by a relatively new instrument, the Er:YAG (erbium: yttrium-aluminum-garnet) laser.Material and methods. Thirty bovine mandibular incisors were reduced to an enamel/dentin thickness of 2.5 mm. Class V preparations were completed to a depth of 2.0 mm, measured with a caliper or by a mark oil the burs. A thermocouple was placed inside the pulp chamber to determine temperature increases (degreesC). Analysis was performed on the following groups (n = 10): Group 1, high-speed handpiece without water cooling, Group 11, high-speed handpiece with water cooling (30 mL/min), and Group III, the noncontact Er:YAG laser (2.94 mum at 350 mJ/10 Hz) with water cooling (4.5 mL/min). The temperature increases were recorded by a computer linked to the thermocouples. The data were analyzed using the Kruskal-Wallis test. The Dunn multiple comparison test was used as post hoc test (alpha = .05).Results. The average temperature rises were: 11.64degreesC (+/-4.35) for Group 1, 0.96degreesC (+/-0.71) for Group 11, and 2.69degreesC (+/-1.12) for Group III. There were no statistical differences between Groups 11 and III, both 11 and III differed from Group I significantly (P = .000 and P = .002, respectively).Conclusion. The preparations made with the high-speed and the laser instrument generated similar heat increases under water cooling. Water cooling was essential to avoid destructive temperature increases when using both the high-speed handpiece and laser.

Temperature rise in cavities prepared by high and low torque handpieces and Er : YAG laser

Objective The aim of this study was to compare intrapulpal temperature increases produced by a high-speed high-torque (speed-increasing) handpiece, a high-speed low-torque handpiece (air-turbine) and an Er: YAG (Erbium: Yttrium-Aluminum-Garnet) laser. Subject and methods Thirty bovine incisors were reduced to a dentine thickness of 2.0 mm. Class V preparations were prepared to a depth of 1.5 mm, measured with a caliper or by a mark on the burs. A thermocouple was placed inside the pulp chamber to determine temperature increases (C). Analysis was performed on the following groups (n = 10) treated with: G1, low-torque handpiece; G2, high-torque handpiece; and G3, Er: YAG laser (2.94 mu m at 250 mJ/4 Hz), all with water cooling. The temperature increases were recorded with a computer linked to the thermocouples. Results The data were submitted to ANOVA and Tukey statistical test. The average temperature rises were: 1.92 +/- 0.80 degrees C for G1, 1.34 +/- 0.86 degrees C for G2, and 0.75 +/- 0.39 degrees C for G3. There were significant statistical differences among the groups (p = 0.095). All the groups tested did not have a change of temperature that exceeds the threshold of 5.5 degrees C. Conclusion Temperature response to the low and high torque handpieces seemed to be similar, however the Er: YAG laser generated a lower temperature rise.