998 resultados para summer mortality


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Background: Previous studies have found high temperatures increase the risk of mortality in summer. However, little is known about whether a sharp decrease or increase in temperature between neighbouring days has any effect on mortality. Method: Poisson regression models were 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. The temperature change was calculated as the current day’s mean temperature minus the previous day’s mean. Results: In Brisbane, a drop of more than 3 °C in temperature between days was associated with relative risks (RRs) of 1.157 (95% confidence interval (CI): 1.024, 1.307) for total non external mortality (NEM), 1.186 (95%CI: 1.002, 1.405) for NEM in females, and 1.442 (95%CI: 1.099, 1.892) for people aged 65–74 years. An increase of more than 3 °C was associated with RRs of 1.353 (95%CI: 1.033, 1.772) for cardiovascular mortality and 1.667 (95%CI: 1.146, 2.425) for people aged < 65 years. In Los Angeles, only a drop of more than 3 °C was significantly associated with RRs of 1.133 (95%CI: 1.053, 1.219) for total NEM, 1.252 (95%CI: 1.131, 1.386) for cardiovascular mortality, and 1.254 (95%CI: 1.135, 1.385) for people aged ≥75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. Conclusion : A significant change in temperature of more than 3 °C, whether positive or negative, has an adverse impact on mortality even after controlling for the current temperature.

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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.

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Objectives Heatwaves can have significant health consequences resulting in increased mortality and morbidity. However, their impact on people living in tropical/subtropical regions remains largely unknown. This study assessed the impact of heatwaves on mortality and emergency hospital admissions (EHAs) from non-external causes (NEC) in Brisbane, a subtropical city in Australia. Methods We acquired daily data on weather, air pollution and EHAs for patients aged 15 years and over in Brisbane between January 1996 and December 2005, and on mortality between January 1996 and November 2004. A locally derived definition of heatwave (daily maximum ≥37°C for 2 or more consecutive days) was adopted. Case–crossover analyses were used to assess the impact of heatwaves on cause-specific mortality and EHAs. Results During heatwaves, there was a statistically significant increase in NEC mortality (OR 1.46; 95% CI 1.21 to 1.77), cardiovascular mortality (OR 1.89; 95% CI 1.44 to 2.48), diabetes mortality in those aged 75+ (OR 9.96; 95% CI 1.02 to 96.85), NEC EHAs (OR 1.15; 95% CI 1.07 to 1.23) and EHAs from renal diseases (OR 1.41; 95% CI 1.09 to 1.83). The elderly were found to be particularly vulnerable to heatwaves (eg, for NEC EHAs, OR 1.24 for 65–74-year-olds and 1.39 for those aged 75+). Conclusions Significant increases in NEC mortality and EHAs were observed during heatwaves in Brisbane where people are well accustomed to hot summer weather. The most vulnerable were the elderly and people with cardiovascular, renal or diabetic disease.

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The life history strategies of massive Porites corals make them a valuable resource not only as key providers of reef structure, but also as recorders of past environmental change. Yet recent documented evidence of an unprecedented increase in the frequency of mortality in Porites warrants investigation into the history of mortality and associated drivers. To achieve this, both an accurate chronology and an understanding of the life history strategies of Porites are necessary. Sixty-two individual Uranium–Thorium (U–Th) dates from 50 dead massive Porites colonies from the central inshore region of the Great Barrier Reef (GBR) revealed the timing of mortality to have occurred predominantly over two main periods from 1989.2 ± 4.1 to 2001.4 ± 4.1, and from 2006.4 ± 1.8 to 2008.4 ± 2.2 A.D., with a small number of colonies dating earlier. Overall, the peak ages of mortality are significantly correlated with maximum sea-surface temperature anomalies. Despite potential sampling bias, the frequency of mortality increased dramatically post-1980. These observations are similar to the results reported for the Southern South China Sea. High resolution measurements of Sr/Ca and Mg/Ca obtained from a well preserved sample that died in 1994.6 ± 2.3 revealed that the time of death occurred at the peak of sea surface temperatures (SST) during the austral summer. In contrast, Sr/Ca and Mg/Ca analysis in two colonies dated to 2006.9 ± 3.0 and 2008.3 ± 2.0, suggest that both died after the austral winter. An increase in Sr/Ca ratios and the presence of low Mg-calcite cements (as determined by SEM and elemental ratio analysis) in one of the colonies was attributed to stressful conditions that may have persisted for some time prior to mortality. For both colonies, however, the timing of mortality coincides with the 4th and 6th largest flood events reported for the Burdekin River in the past 60 years, implying that factors associated with terrestrial runoff may have been responsible for mortality. Our results show that a combination of U–Th and elemental ratio geochemistry can potentially be used to precisely and accurately determine the timing and season of mortality in modern massive Porites corals. For reefs where long-term monitoring data are absent, the ability to reconstruct historical events in coral communities may prove useful to reef managers by providing some baseline knowledge on disturbance history and associated drivers.

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Seasonal patterns in mortality have been recognised for decades, with a marked excess of deaths in winter, yet our understanding of the causes of this phenomenon is not yet complete. Research has shown that low and high temperatures are associated with increased mortality independently of season; however, the impact of unseasonal weather on mortality has been less studied. In this study, we aimed to determine if unseasonal patterns in weather were associated with unseasonal patterns in mortality. We obtained daily temperature, humidity and mortality data from 1988 to 2009 for five major Australian cities with a range of climates. We split the seasonal patterns in temperature, humidity and mortality into their stationary and non-stationary parts. A stationary seasonal pattern is consistent from year-to-year, and a non-stationary pattern varies from year-to-year. We used Poisson regression to investigate associations between unseasonal weather and an unusual number of deaths. We found that deaths rates in Australia were 20–30% higher in winter than summer. The seasonal pattern of mortality was non-stationary, with much larger peaks in some winters. Winters that were colder or drier than a typical winter had significantly increased death risks in most cities. Conversely summers that were warmer or more humid than average showed no increase in death risks. Better understanding the occurrence and cause of seasonal variations in mortality will help with disease prevention and save lives.

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In south-eastern Queensland, Australia, sorghum planted in early spring usually escapes sorghum midge, Stenodiplosis sorghicola, attack. Experiments were conducted to better understand the role of winter diapause in the population dynamics of this pest. Emergence patterns of adult midge from diapausing larvae on the soil surface and at various depths were investigated during spring to autumn of 1987/88–1989/90. From 1987/88 to 1989/90, 89%, 65% and 98% of adult emergence, respectively, occurred during November and December. Adult emergence from larvae diapausing on the soil surface was severely reduced due to high mortality attributed to surface soil temperatures in excess of 40°C, with much of this mortality occurring between mid-September and mid-October. Emergence of adults from the soil surface was considerably delayed in the 1988/89 season compared with larvae buried at 5 or 10 cm which had similar emergence patterns for all three seasons. In 1989/90, when a 1-cm-deep treatment was included, there was a 392% increase in adult emergence from this treatment compared with deeper treatments. Some diapausing larvae on the surface did not emerge at the end of summer in only 1 year (1989/90), when 28.0% of the larvae on the surface remained in diapause, whereas only 0.8% of the buried larvae remained in diapause. We conclude that the pattern of emergence explains why spring plantings of sorghum in south-eastern Queensland usually escape sorghum midge attack.

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Surveys were conducted between 1997 and 2001 to investigate the incidence of overwintering Helicoverpa spp. pupae under summer crop residues on the Darling Downs, Queensland. Only Helicoverpa armigera was represented in collections of overwintering pupae. The results indicated that late-season crops of cotton, sorghum, maize, soybean, mungbean and sunflower were equally likely to have overwintering pupae under them. In the absence of tillage practices, these crops had the potential to produce similar numbers of moths/ha in the spring. There were expected differences between years in the densities of overwintering pupae and the number of emerged moths/ha. Irrigated crops produced 2.5 times more moths/ha than dryland crops. Overall survival from autumn-formed pupae to emerged moths averaged 44%, with a higher proportion of pupae under maize surviving to produce moths than each of the other crops. Parasitoids killed 44.1% of pupae, with Heteropelma scaposum representing 83.3% of all parasitoids reared from pupae. Percentage parasitism levels were lower in irrigated crops (27.6%) compared with dryland crops (40.5%). Recent changes to Helicoverpa spp. management in cotton/grain-farming systems in south-eastern Queensland, including widespread adoption of Bt cotton, and use of more effective and more selective insecticides, could lead to lower densities of overwintering pupae under late summer crops.

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Anadromous whitefish is one of the most important fish species in the Finnish coastal fisheries in the Gulf fo Bothnia. To compensate the lost reproduction due to river damming and to support the fisheries, several million one-summer old whitefish are released yearly into the Gulf of Bothnia. Since there are naturally reproducing whitefish in the Gulf as well, and the wild and stocked fish can not be separated in the catch, stocking impact can only be estimated by marking the stocked fish. Due to the small size and large number of released whitefish, the scattered fishery and large area where the whitefish migrate, most of the traditionally used fish marking methods were either unsuitable (e.g. Carlin-tags) or proved to be too expensive (e.g. coded wire tags). Fluorescent pigment spraying method offers a fast and cost-effective method to mass-mark young fish. However, the results are not always satisfactory due to low long-time retention of the marks in some species. The method has to be tested and proper marking conditions and methods determined for each species. This thesis is based on work that was accomplished while developing the fluorescent pigment spraying method for marking one-summer old whitefish fingerlings, and it draws together the results of mass-marking whitefish fingerlings that were released in the Gulf of Bothnia. Fluorescent pigment spraying method is suitable for one-summer old whitefish larger than 8 cm total length. The water temperature during the marking should not exceed 10o C. Suitable spraying pressure is 6 bars measured in the compressor outlet, and the distance of the spraying gun nozzle should be ca 20 cm from the fish. Under such conditions, the marking results in long-term retention of the mark with low or no mortality. The stress level of the fish (measured as muscle water content) rises during the marking procedure, but if the fish are allowed to recover after marking, the overall stress level remains within the limits observed in normal fish handling during the capture-loading-transport-stocking procedure. The marked whitefish fingerlings are released into the sea at larger size and later in the season than the wild whitefish. However, the stocked individuals migrate to the southern feeding grounds in a similar pattern to the wild ones. The catch produced by whitefish stocking in the Gulf of Bothnia varied between released fingerling groups, but was within the limits reported elsewhere in Finland. The releases in the southern Bothnian Bay resulted in a larger catch than those made in the northern Bothnian Bay. The size of the released fingerlings seemed to have some effect on survival of the fish during the first winter in the sea. However, when the different marking groups were compared, the mean fingerling size was not related to stocking success.

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Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden. Methods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization. Results: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south-north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918-19, but different factors explained mortality variation in each wave. Conclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.

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Length-based methods (LBMs) were used to study the growth of Trisopterus minutus capelanus in the Strait of Sicily (Messina Strait). A total of 16,304 'merluzzetto' or poor cod collected by experimental trawling off the southern coast of Sicily during spring, summer, autumn 1986 and winter 1987 were measured in order to estimate the length structure of the population. Length-frequency distribution were analyzed and normal components were discriminated. Von Bertalanffy growth parameters were derived from the mean length of the normal components. The growth parameters obtained by weighted non-linear regression were: K=0.462 (yr super(1)), L sub( infinity )=222.3 (TL,mm) and t sub(o)=-0.679 yr. The resulting growth performance index ( Phi ') was 4.36, a value slightly lower than those derived for Western Mediterranean (mean Phi '=4.45) and Adriatic ( Phi '=4.58) populations and slightly higher than that derived for Hellenic waters ( Phi '=4.27). On the basis of the von Bertalanffy parameters estimated, an array of age-specific instantaneous natural mortality rate (M sub(t)=0.5-1.1) and an average value of total natural mortality rate (Z=2.1 yr super(1)) were estimated and used in the Thompson and Bell yield per recruit (Y/R) analysis in order to evaluate the status of the fishery and forecast the effects of changes in the fishing pattern. Results indicate that this resource is overexploited and that Y/R could be increased by postponing the age at first capture from 0.5 to 1.0 yr. Even a slight reduction in fishing mortality could improve the performance of the fishery. At the present level of exploitation, and assuming a constant recruitment, the spawning stock biomass per recruit (SPR) is well below the conservative threshold of 30% of the pristine or unexploited SPR.

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Age, growth and mortality of the toadfish, Halobatrachus didactylus, were determined by examination of the whole sagittal otoliths of fish sampled in the Bay of Cádiz (southwestern Spain) from March 1999 to March 2000. A total of 844 specimens (425 males, 416 females, and 3 of indeterminate sex), ranging from 95 to 470 mm in total length were examined. Eighty-nine percent of the otoliths could be read allowing an age estimation. The opaque zone was formed between April and May coincident with the maximum reproductive peak, while the translucent zone formed mainly in summer-fall (June to December). Maximum ages for males and females were 12 and 10 years, respectively. The samples were dominated by 2- to 6-year-old specimens. Males matured at an age of approximately 2 years and females at 3 years. Fish total length and otolith radius were closely related. The von Bertalanffy growth curve was used to describe growth. The parameters were derived from back-calculated length-at-age. Significant differences in the growth parameters were found between sexes. Although the growth analysis revealed that this species is slow-growing, males reached larger sizes than females. Females appeared to experience higher natural mortality rates than males.

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Increasing interest in the use of stock enhancement as a management tool necessitates a better understanding of the relative costs and benefits of alternative release strategies. We present a relatively simple model coupling ecology and economic costs to make inferences about optimal release scenarios for summer flounder (Paralichthys dentatus), a subject of stock enhancement interest in North Carolina. The model, parameterized from mark-recapture experiments, predicts optimal release scenarios from both survival and economic standpoints for varyious dates-of-release, sizes-at-release, and numbers of fish released. Although most stock enhancement efforts involve the release of relatively small fish, the model suggests that optimal results (maximum survival and minimum costs) will be obtained when relatively large fish (75–80 mm total length) are released early in the nursery season (April). We investigated the sensitivity of model predictions to violations of the assumption of density-independent mortality by including density-mortality relationships based on weak and strong type-2 and type-3 predator functional responses (resulting in depensatory mortality at elevated densities). Depending on postrelease density, density-mortality relationships included in the model considerably affect predicted postrelease survival and economic costs associated with enhancement efforts, but do not alter the release scenario (i.e. combination of release variables) that produces optimal results. Predicted (from model output) declines in flounder over time most closely match declines observed in replicate field sites when mortality in the model is density-independent or governed by a weak type-3 functional response. The model provides an example of a relatively easy-to-develop predictive tool with which to make inferences about the ecological and economic potential of stock enhancement of summer flounder and provides a template for model creation for additional species that are subjects of stock enhancement interest, but for which limited empirical data exist.

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Octopuses are commonly taken as bycatch in many trap fisheries for spiny lobsters (Decapoda: Palinuridae) and can cause significant levels of within-trap lobster mortality. This article describes spatiotemporal patterns for Maori octopus (Octopus maorum) catch rates and rock lobster (Jasus edwardsii) mortality rates and examines factors that are associated with within-trap lobster mortality in the South Australian rock lobster fishery (SARLF). Since 1983, between 38,000 and 119,000 octopuses per annum have been taken in SARLF traps. Catch rates have fluctuated between 2.2 and 6.2 octopus/100 trap-lifts each day. There is no evidence to suggest that catch rates have declined or that this level of bycatch is unsustainable. Over the last five years, approximately 240,000 lobsters per annum have been killed in traps, representing ~4% of the total catch. Field studies show that over 98% of within-trap lobster mortality is attributable to octopus predation. Lobster mortality rates are positively correlated with the catch rates of octopus. The highest octopus catch rates and lobster mortality rates are recorded during summer and in the more productive southern zone of the fishery. In the southern zone, within-trap lobster mortality rates have increased in recent years, apparently in response to the increase in the number of lobsters in traps and the resultant increase in the probability of octopus encountering traps containing one or more lobsters. Lobster mortality rates are also positively correlated with soak-times in the southern zone fishery and with lobster size. Minimizing trap soak-times is one method currently available for reducing lobster mortality rates. More significant reductions in the rates of within-trap lobster mortality may require a change in the design of lobster traps.

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Objective: To investigate the association between serum 25-hydroxyvitamin D concentrations (25(OH)D) and mortality in a large consortium of cohort studies paying particular attention to potential age, sex, season, and country differences.

Design: Meta-analysis of individual participant data of eight prospective cohort studies from Europe and the US.

Setting: General population.

Participants: 26 018 men and women aged 50-79 years

Main outcome measures: All-cause, cardiovascular, and cancer mortality.

Results: 25(OH)D concentrations varied strongly by season (higher in summer), country (higher in US and northern Europe) and sex (higher in men), but no consistent trend with age was observed. During follow-up, 6695 study participants died, among whom 2624 died of cardiovascular diseases and 2227 died of cancer. For each cohort and analysis, 25(OH)D quintiles were defined with cohort and subgroup specific cut-off values. Comparing bottom versus top quintiles resulted in a pooled risk ratio of 1.57 (95% CI 1.36 to 1.81) for all-cause mortality. Risk ratios for cardiovascular mortality were similar in magnitude to that for all-cause mortality in subjects both with and without a history of cardiovascular disease at baseline. With respect to cancer mortality, an association was only observed among subjects with a history of cancer (risk ratio, 1.70 (1.00 to 2.88)). Analyses using all quintiles suggest curvilinear, inverse, dose-response curves for the aforementioned relationships. No strong age, sex, season, or country specific differences were detected. Heterogeneity was low in most meta-analyses.

Conclusions: Despite levels of 25(OH)D strongly varying with country, sex, and season, the association between 25(OH)D level and all-cause and cause-specific mortality was remarkably consistent. Results from a long term randomised controlled trial addressing longevity are being awaited before vitamin D supplementation can be recommended in most individuals with low 25(OH)D levels.

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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).