975 resultados para Skin temperature


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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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OBJECTIVE: This paper reviews the epidemiological evidence on the relationship between ambient temperature and morbidity. It assesses the methodological issues in previous studies, and proposes future research directions. DATA SOURCES AND DATA EXTRACTION: We searched the PubMed database for epidemiological studies on ambient temperature and morbidity of non-communicable diseases published in refereed English journals prior to June 2010. 40 relevant studies were identified. Of these, 24 examined the relationship between ambient temperature and morbidity, 15 investigated the short-term effects of heatwave on morbidity, and 1 assessed both temperature and heatwave effects. DATA SYNTHESIS: Descriptive and time-series studies were the two main research designs used to investigate the temperature–morbidity relationship. Measurements of temperature exposure and health outcomes used in these studies differed widely. The majority of studies reported a significant relationship between ambient temperature and total or cause-specific morbidities. However, there were some inconsistencies in the direction and magnitude of non-linear lag effects. The lag effect of hot temperature on morbidity was shorter (several days) compared to that of cold temperature (up to a few weeks). The temperature–morbidity relationship may be confounded and/or modified by socio-demographic factors and air pollution. CONCLUSIONS: There is a significant short-term effect of ambient temperature on total and cause-specific morbidities. However, further research is needed to determine an appropriate temperature measure, consider a diverse range of morbidities, and to use consistent methodology to make different studies more comparable.

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Extreme temperatures have been shown to have a detrimental effect on health. Hot temperatures can increase the risk of mortality, particularly in people suffering from cardiorespiratory diseases. Given the onset of climate change, it is critical that the impact of temperature on health is understood, so that effective public health strategies can correctly identify vulnerable groups within the population. However, while effects on mortality have been extensively studied, temperature–related morbidity has received less attention. This study applied a systematic review and meta–analysis to examine the current literature relating to hot temperatures and morbidity.

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The majority of small-cell lung cancers (SCLCs) express p16 but not pRb. Given our previous study showing loss of pRb in Merkel cell carcinoma (MCC)/neuroendocrine carcinoma of the skin and the clinicopathological similarities between SCLC and MCC, we wished to determine if this was also the case in MCC. Twenty-nine MCC specimens from 23 patients were examined for deletions at 10 loci on 9p and 1 on 9q. No loss of heterozygosity (LOH) was seen in 9 patients including 2 for which tumour and cell line DNAs were examined. Four patients had LOH for all informative loci on 9p. Ten tumours showed more limited regions of loss on 9p, and from these 2 common regions of deletion were determined. Half of all informative cases had LOH at D9S168, the most telomeric marker examined, and 3 specimens showed loss of only D9S168. A second region (IFNA-D9S126) showed LOH in 10 (44%) cases, and case MCC26 showed LOH for only D9S126, implicating genes centromeric of the CDKN2A locus. No mutations in the coding regions of p16 were seen in 7 cell lines tested, and reactivity to anti-p16 antibody was seen in all 11 tumour specimens examined and in 6 of 7 cell lines from 6 patients. Furthermore, all cell lines examined reacted with anti-p14(ARF) antibody. These results suggest that neither transcript of the CDKN2A locus is the target of deletions on 9p in MCC and imply the existence of tumour-suppressor genes mapping both centromeric and telomeric of this locus.

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The uncertainty associated with how projected climate change will affect global C cycling could have a large impact on predictions of soil C stocks. The purpose of our study was to determine how various soil decomposition and chemistry characteristics relate to soil organic matter (SOM) temperature sensitivity. We accomplished this objective using long-term soil incubations at three temperatures (15, 25, and 35°C) and pyrolysis molecular beam mass spectrometry (py-MBMS) on 12 soils from 6 sites along a mean annual temperature (MAT) gradient (2–25.6°C). The Q10 values calculated from the CO2 respired during a long-term incubation using the Q10-q method showed decomposition of the more resistant fraction to be more temperature sensitive with a Q10-q of 1.95 ± 0.08 for the labile fraction and a Q10-q of 3.33 ± 0.04 for the more resistant fraction. We compared the fit of soil respiration data using a two-pool model (active and slow) with first-order kinetics with a three-pool model and found that the two and three-pool models statistically fit the data equally well. The three-pool model changed the size and rate constant for the more resistant pool. The size of the active pool in these soils, calculated using the two-pool model, increased with incubation temperature and ranged from 0.1 to 14.0% of initial soil organic C. Sites with an intermediate MAT and lowest C/N ratio had the largest active pool. Pyrolysis molecular beam mass spectrometry showed declines in carbohydrates with conversion from grassland to wheat cultivation and a greater amount of protected carbohydrates in allophanic soils which may have lead to differences found between the total amount of CO2 respired, the size of the active pool, and the Q10-q values of the soils.

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Background: Queensland men aged 50 years and older are at high risk for melanoma. Early detection via skin self examination (SSE) (particularly whole-body SSE) followed by presentation to a doctor with suspicious lesions, may decrease morbidity and mortality from melanoma. Prevalence of whole-body SSE (wbSSE) is lower in Queensland older men compared to other population subgroups. With the exception of the present study no previous research has investigated the determinants of wbSSE in older men, or interventions to increase the behaviour in this population. Furthermore, although past SSE intervention studies for other populations have cited health behaviour models in the development of interventions, no study has tested these models in full. The Skin Awareness Study: A recent randomised trial, called the Skin Awareness Study, tested the impact of a video-delivered intervention compared to written materials alone on wbSSE in men aged 50 years or older (n=930). Men were recruited from the general population and interviewed over the telephone at baseline and 13 months. The proportion of men who reported wbSSE rose from 10% to 31% in the control group, and from 11% to 36% in the intervention group. Current research: The current research was a secondary analysis of data collected for the Skin Awareness Study. The objectives were as follows: • To describe how men who did not take up any SSE during the study period differed from those who did take up examining their skin. • To determine whether the intervention program was successful in affecting the constructs of the Health Belief Model it was aimed at (self-efficacy, perceived threat, and outcome expectations); and whether this in turn influenced wbSSE. • To determine whether the Health Action Process Approach (HAPA) was a better predictor of wbSSE behaviour compared to the Health Belief Model (HBM). Methods: For objective 1, men who did not report any past SSE at baseline (n=308) were categorised as having ‘taken up SSE’ (reported SSE at study end) or ‘resisted SSE’ (reported no SSE at study end). Bivariate logistic regression, followed by multivariable regression, investigated the association between participant characteristics measured at baseline and resisting SSE. For objective 2 proxy measures of self-efficacy, perceived threat, and outcome expectations were selected. To determine whether these mediated the effect of the intervention on the outcome, a mediator analysis was performed with all participants who completed interviews at both time points (n=830) following the Baron and Kenny approach, modified for use with structural equation modelling (SEM). For objective 3, control group participants only were included (n=410). Proxy measures of all HBM and HAPA constructs were selected and SEM was used to build up models and test the significance of each hypothesised pathway. A likelihood ratio test compared the HAPA to the HBM. Results: Amongst men who did not report any SSE at baseline, 27% did not take up any SSE by the end of the study. In multivariable analyses, resisting SSE was associated with having more freckly skin (p=0.027); being unsure about the statement ‘if I saw something suspicious on my skin, I’d go to the doctor straight away’ (p=0.028); not intending to perform SSE (p=0.015), having lower SSE self-efficacy (p<0.001), and having no recommendation for SSE from a doctor (p=0.002). In the mediator analysis none of the tested variables mediated the relationship between the intervention and wbSSE. In regards to health behaviour models, the HBM did not predict wbSSE well overall. Only the construct of self-efficacy was a significant predictor of future wbSSE (p=0.001), while neither perceived threat (p=0.584) nor outcome expectations (p=0.220) were. By contrast, when the HAPA constructs were added, all three HBM variables predicted intention to perform SSE, which in turn predicted future behaviour (p=0.015). The HAPA construct of volitional self-efficacy was also associated with wbSSE (p=0.046). The HAPA was a significantly better model compared to the HBM (p<0.001). Limitations: Items selected to measure HBM and HAPA model constructs for objectives 2 and 3 may not have accurately reflected each construct. Conclusions: This research added to the evidence base on how best to target interventions to older men; and on the appropriateness of particular health behaviour models to guide interventions. Findings indicate that to overcome resistance those men with more negative pre-existing attitudes to SSE (not intending to do it, lower initial self-efficacy) may need to be targeted with more intensive interventions in the future. Involving general practitioners in recommending SSE to their patients in this population, alongside disseminating an intervention, may increase its success. Comparison of the HBM and HAPA showed that while two of the three HBM variables examined did not directly predict future wbSSE, all three were associated with intention to self-examine skin. This suggests that in this population, intervening on these variables may increase intention to examine skin, but not necessarily the behaviour itself. Future interventions could potentially focus on increasing both the motivational variables of perceived threat and outcome expectations as well as a combination of both action and volitional self-efficacy; with the aim of increasing intention as well as its translation to taking up and maintaining regular wbSSE.

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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.