959 resultados para epidemiology


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The objective of this study was to test for the measurement invariance of the Attention and Thought Problems subscales of the Child Behavior Checklist (CBCL) and Youth Self-Report (YSR) in a population-based sample of adolescents with and without epilepsy. Data were obtained from the 14-year follow-up of the Mater University Study of Pregnancy in which 33 adolescents with epilepsy and 1068 healthy controls were included for analysis. Confirmatory factor analysis was used to test for measurement invariance between adolescents with and without epilepsy. Structural equation modeling was used to test for group differences in attention and thought problems as measured with the CBCL and YSR. Measurement invariance was demonstrated for the original CBCL Attention Problems and YSR Thought Problems. After the removal of ambiguous items (“confused” and “daydreams”),measurement invariance was established for the YSR Attention Problems. The original and reduced CBCL Thought Problems were noninvariant. Adolescents with epilepsy had significantly more symptoms of behavioral problems on the CBCL Attention Problems, β = 0.51, p = 0.002, compared with healthy controls. In contrast, no significant differences were found for the YSR Attention and Thought Problems, β = −0.11, p = 0.417 and β = −0.20, p = 0.116, respectively. In this population-based sample of adolescents with epilepsy, the CBCL Attention Problems and YSR Thought Problems appear to be valid measures of behavioral problems, whereas the YSR Attention Problems was valid only after the removal of ambiguous items. Replication of these findings in clinical samples of adolescents with epilepsy that overcome the limitations of the current study is warranted.

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Purpose: This is one of the first studies to report that the Achenbach internalising scales were much more effective at identifying those with current comorbid depression and anxiety, rather than individual mood disorder. Introduction: The Achenbach behaviour checklists (YSR,YASR) are widely used, low cost screening tools used to assess problem behaviour. Several studies report good association between the checklists and psychiatric diagnoses; although with varying degrees of agreement. Most are cross-sectional studies involving adolescents referred to mental health services; few are in large community-based studies. This study examined the usefulness of the Achenbach internalising scales in the primary screening (both predictive and concurrent)for depression and anxiety. Methods: The sample was 2400 young adults from an Australian population-based prospective birth cohort study. The association between the empirical anxiety and depression scales were individually assessed against DSM-IV depression and anxiety diagnoses. Odds ratios and diagnostic efficiency tests report the findings. Results: Adolescents with internalising symptoms were twice (OR 2.3, 95%CI 1.7 to 3.1) as likely to be diagnosed with later DSM-IV depression. YASR internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. The internalising scales were much more effective at identifying those with comorbid depression and anxiety. Conclusions: Adolescence and early adulthood are key risk periods for the onset of anxiety and depression. This study found that young people with internalising behaviour problems were more likely to have comorbid depression and anxiety DSM-IV disorder.

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Police reported crash data are the primary source of crash information in most jurisdictions. However, the definition of serious injury within police-reported data is not consistent across jurisdictions and may not be accurate. With the Australian National Road Safety Strategy targeting the reduction of serious injuries, there is a greater need to assess the accuracy of the methods used to identify these injuries. A possible source of more accurate information relating to injury severity is hospital data. While other studies have compared police and hospital data to highlight the under-reporting in police-reported data, little attention has been given to the accuracy of the methods used by police to identify serious injuries. The current study aimed to assess how accurate the identification of serious injuries is in police-reported crash data, by comparing the profiles of transport-related injuries in the Queensland Road Crash Database with an aligned sample of data from the Queensland Hospital Admitted Patients Data Collection. Results showed that, while a similar number of traffic injuries were recorded in both data sets, the profile of these injuries was different based on gender, age, location, and road user. The results suggest that the ‘hospitalisation’ severity category used by police may not reflect true hospitalisations in all cases. Further, it highlights the wide variety of severity levels within hospitalised cases that are not captured by the current police-reported definitions. While a data linkage study is required to confirm these results, they highlight that a reliance on police-reported serious traffic injury data alone could result in inaccurate estimates of the impact and cost of crashes and lead to a misallocation of valuable resources.

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The aim of this study was to examine whether takeaway food consumption mediated (explained) the association between socioeconomic position and body mass index (BMI). A postal-survey was conducted among 1500 randomly selected adults aged between 25 and 64 years in Brisbane, Australia during 2009 (response rate 63.7%, N=903). BMI was calculated using self-reported weight and height. Participants reported usual takeaway food consumption, and these takeaway items were categorised into "healthy" and "less healthy" choices. Socioeconomic position was ascertained by education, household income, and occupation. The mean BMI was 27.1kg/m(2) for men and 25.7kg/m(2) for women. Among men, none of the socioeconomic measures were associated with BMI. In contrast, women with diploma/vocational education (β=2.12) and high school only (β=2.60), and those who were white-collar (β=1.55) and blue-collar employees (β=2.83) had significantly greater BMI compared with their more advantaged counterparts. However, household income was not associated with BMI. Among women, the consumption of "less healthy" takeaway food mediated BMI differences between the least and most educated, and between those employed in blue collar occupations and their higher status counterparts. Decreasing the consumption of "less healthy" takeaway options may reduce socioeconomic inequalities in overweight and obesity among women but not men.

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Background Transmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China. Methods Plasmodium vivax malaria surveillance data (1991–2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence. Results There was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas. Conclusions The differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.

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Objective:  To examine the space-time clustering of dengue fever (DF) transmission in Bangladesh using geographical information system and spatial scan statistics (SaTScan). Methods:  We obtained data on monthly suspected DF cases and deaths by district in Bangladesh for the period of 2000–2009 from Directorate General of Health Services. Population and district boundary data of each district were collected from national census managed by Bangladesh Bureau of Statistics. To identify the space-time clusters of DF transmission a discrete Poisson model was performed using SaTScan software. Results:  Space-time distribution of DF transmission was clustered during three periods 2000–2002, 2003–2005 and 2006–2009. Dhaka was the most likely cluster for DF in all three periods. Several other districts were significant secondary clusters. However, the geographical range of DF transmission appears to have declined in Bangladesh over the last decade. Conclusion:  There were significant space-time clusters of DF in Bangladesh over the last decade. Our results would prompt future studies to explore how social and ecological factors may affect DF transmission and would also be useful for improving DF control and prevention programs in Bangladesh.

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BACKGROUND Malaria remains a public health problem in the remote and poor area of Yunnan Province, China. Yunnan faces an increasing risk of imported malaria infections from Mekong river neighboring countries. This study aimed to identify the high risk area of malaria transmission in Yunnan Province, and to estimate the effects of climatic variability on the transmission of Plasmodium vivax and Plasmodium falciparum in the identified area. METHODS We identified spatial clusters of malaria cases using spatial cluster analysis at a county level in Yunnan Province, 2005-2010, and estimated the weekly effects of climatic factors on P. vivax and P. falciparum based on a dataset of daily malaria cases and climatic variables. A distributed lag nonlinear model was used to estimate the impact of temperature, relative humidity and rainfall up to 10-week lags on both types of malaria parasite after adjusting for seasonal and long-term effects. RESULTS The primary cluster area was identified along the China-Myanmar border in western Yunnan. A 1°C increase in minimum temperature was associated with a lag 4 to 9 weeks relative risk (RR), with the highest effect at lag 7 weeks for P. vivax (RR = 1.03; 95% CI, 1.01, 1.05) and 6 weeks for P. falciparum (RR = 1.07; 95% CI, 1.04, 1.11); a 10-mm increment in rainfall was associated with RRs of lags 2-4 weeks and 9-10 weeks, with the highest effect at 3 weeks for both P. vivax (RR = 1.03; 95% CI, 1.01, 1.04) and P. falciparum (RR = 1.04; 95% CI, 1.01, 1.06); and the RRs with a 10% rise in relative humidity were significant from lag 3 to 8 weeks with the highest RR of 1.24 (95% CI, 1.10, 1.41) for P. vivax at 5-week lag. CONCLUSIONS Our findings suggest that the China-Myanmar border is a high risk area for malaria transmission. Climatic factors appeared to be among major determinants of malaria transmission in this area. The estimated lag effects for the association between temperature and malaria are consistent with the life cycles of both mosquito vector and malaria parasite. These findings will be useful for malaria surveillance-response systems in the Mekong river region.

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Emerging infectious diseases present a complex challenge to public health officials and governments; these challenges have been compounded by rapidly shifting patterns of human behaviour and globalisation. The increase in emerging infectious diseases has led to calls for new technologies and approaches for detection, tracking, reporting, and response. Internet-based surveillance systems offer a novel and developing means of monitoring conditions of public health concern, including emerging infectious diseases. We review studies that have exploited internet use and search trends to monitor two such diseases: influenza and dengue. Internet-based surveillance systems have good congruence with traditional surveillance approaches. Additionally, internet-based approaches are logistically and economically appealing. However, they do not have the capacity to replace traditional surveillance systems; they should not be viewed as an alternative, but rather an extension. Future research should focus on using data generated through internet-based surveillance and response systems to bolster the capacity of traditional surveillance systems for emerging infectious diseases.

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Previous studies have demonstrated the importance of weather variables in influencing the incidence of influenza. However, the role of air pollution is often ignored in identifying the environmental drivers of influenza. This research aims to examine the impacts of air pollutants and temperature on the incidence of pediatric influenza in Brisbane, Australia. Lab-confirmed daily data on influenza counts among children aged 0-14years in Brisbane from 2001 January 1st to 2008 December 31st were retrieved from Queensland Health. Daily data on maximum and minimum temperatures for the same period were supplied by the Australian Bureau of Meteorology. Winter was chosen as the main study season due to it having the highest pediatric influenza incidence. Four Poisson log-linear regression models, with daily pediatric seasonal influenza counts as the outcome, were used to examine the impacts of air pollutants (i.e., ozone (O3), particulate matter≤10μm (PM10) and nitrogen dioxide (NO2)) and temperature (using a moving average of ten days for these variables) on pediatric influenza. The results show that mean temperature (Relative risk (RR): 0.86; 95% Confidence Interval (CI): 0.82-0.89) was negatively associated with pediatric seasonal influenza in Brisbane, and high concentrations of O3 (RR: 1.28; 95% CI: 1.25-1.31) and PM10 (RR: 1.11; 95% CI: 1.10-1.13) were associated with more pediatric influenza cases. There was a significant interaction effect (RR: 0.94; 95% CI: 0.93-0.95) between PM10 and mean temperature on pediatric influenza. Adding the interaction term between mean temperature and PM10 substantially improved the model fit. This study provides evidence that PM10 needs to be taken into account when evaluating the temperature-influenza relationship. O3 was also an important predictor, independent of temperature.

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OBJECTIVE The aim of the study is to examine the spatiotemporal pattern of Japanese Encephalitis (JE) in mainland China during 2002-2010. Specific objectives of the study were to quantify the temporal variation in incidence of JE cases, to determine if clustering of JE cases exists, to detect high risk spatiotemporal clusters of JE cases and to provide evidence-based preventive suggestions to relevant stakeholders. METHODS Monthly JE cases at the county level in mainland China during 2002-2010 were obtained from the China Information System for Diseases Control and Prevention (CISDCP). For the purpose of the analysis, JE case counts for nine years were aggregated into four temporal periods (2002; 2003-2005; 2006; and 2007-2010). Local Indicators of Spatial Association and spatial scan statistics were performed to detect and evaluate local high risk space-time clusters. RESULTS JE incidence showed a decreasing trend from 2002 to 2005 but peaked in 2006, then fluctuated over the study period. Spatial cluster analysis detected high value clusters, mainly located in Southwestern China. Similarly, we identified a primary spatiotemporal cluster of JE in Southwestern China between July and August, with the geographical range of JE transmission increasing over the past years. CONCLUSION JE in China is geographically clustered and its spatial extent dynamically changed during the last nine years in mainland China. This indicates that risk factors for JE infection are likely to be spatially heterogeneous. The results may assist national and local health authorities in the development/refinement of a better preventive strategy and increase the effectiveness of public health interventions against JE transmission.

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BACKGROUND Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. METHODS/PRINCIPAL FINDINGS We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. CONCLUSIONS/SIGNIFICANCE We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

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China's National Health and Family Planning Commission announced 3 deaths caused by avian-origin influenza A(H7N9) virus in March, which was the first time that the H7N9 strain has been found in humans [1]. This is of major public health significance and raises urgent questions and global concerns [2, 3]. To explore epidemic characteristics of human infections with H7N9 virus, data on individual cases from 19 February 2013 (onset date of first case) to 14 April 2013 were collected from the China Information System for Disease Control and Prevention, which included information about sex; age; occupation; residential address; and day of symptom onset, diagnosis, and outcome for each case. The definition of an unconfirmed probable H7N9 case is a patient with epidemiologic evidence of contact …

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OBJECTIVES To identify the meteorological drivers of dengue vector density and determine high- and low-risk transmission zones for dengue prevention and control in Cairns, Australia. METHODS Weekly adult female Ae. aegypti data were obtained from 79 double sticky ovitraps (SOs) located in Cairns for the period September 2007-May 2012. Maximum temperature, total rainfall and average relative humidity data were obtained from the Australian Bureau of Meteorology for the study period. Time series-distributed lag nonlinear models were used to assess the relationship between meteorological variables and vector density. Spatial autocorrelation was assessed via semivariography, and ordinary kriging was undertaken to predict vector density in Cairns. RESULTS Ae. aegypti density was associated with temperature and rainfall. However, these relationships differed between short (0-6 weeks) and long (0-30 weeks) lag periods. Semivariograms showed that vector distributions were spatially autocorrelated in September 2007-May 2008 and January 2009-May 2009, and vector density maps identified high transmission zones in the most populated parts of Cairns city, as well as Machans Beach. CONCLUSION Spatiotemporal patterns of Ae. aegypti in Cairns are complex, showing spatial autocorrelation and associations with temperature and rainfall. Sticky ovitraps should be placed no more than 1.2 km apart to ensure entomological coverage and efficient use of resources. Vector density maps provide evidence for the targeting of prevention and control activities. Further research is needed to explore the possibility of developing an early warning system of dengue based on meteorological and environmental factors.

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BACKGROUND Dengue fever (DF) outbreaks often arise from imported DF cases in Cairns, Australia. Few studies have incorporated imported DF cases in the estimation of the relationship between weather variability and incidence of autochthonous DF. The study aimed to examine the impact of weather variability on autochthonous DF infection after accounting for imported DF cases and then to explore the possibility of developing an empirical forecast system. METHODOLOGY/PRINCIPAL FINDS Data on weather variables, notified DF cases (including those acquired locally and overseas), and population size in Cairns were supplied by the Australian Bureau of Meteorology, Queensland Health, and Australian Bureau of Statistics. A time-series negative-binomial hurdle model was used to assess the effects of imported DF cases and weather variability on autochthonous DF incidence. Our results showed that monthly autochthonous DF incidences were significantly associated with monthly imported DF cases (Relative Risk (RR):1.52; 95% confidence interval (CI): 1.01-2.28), monthly minimum temperature ((o)C) (RR: 2.28; 95% CI: 1.77-2.93), monthly relative humidity (%) (RR: 1.21; 95% CI: 1.06-1.37), monthly rainfall (mm) (RR: 0.50; 95% CI: 0.31-0.81) and monthly standard deviation of daily relative humidity (%) (RR: 1.27; 95% CI: 1.08-1.50). In the zero hurdle component, the occurrence of monthly autochthonous DF cases was significantly associated with monthly minimum temperature (Odds Ratio (OR): 1.64; 95% CI: 1.01-2.67). CONCLUSIONS/SIGNIFICANCE Our research suggested that incidences of monthly autochthonous DF were strongly positively associated with monthly imported DF cases, local minimum temperature and inter-month relative humidity variability in Cairns. Moreover, DF outbreak in Cairns was driven by imported DF cases only under favourable seasons and weather conditions in the study.

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Severe fever with thrombocytopenia syndrome (SFTS), an emerging vector-borne disease, is caused by a novel bunyavirus belonging to the genus Phlebovirus [1, 2]. SFTS infections can be life-threatening and are characterized by sudden onset of fever, thrombocytopenia, gastrointestinal symptoms, and leukocytopenia. The tick Haemaphysalis longicornis is generally considered to be the vector of SFTS, which is widely distributed in China [2]. Person-to-person transmission through direct contact with contaminated blood has also been reported as a possible means of SFTS transmission [3–5]. Currently, there is no specific treatment other than supportive care [6]...