Climate variability and hemorrhagic fever with renal syndrome transmission in northeastern China

Background: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by climatic variables. However, few studies have examined the quantitative relationship between climate variation and HFRS transmission. ---------- Objective: We examined the potential impact of climate variability on HFRS transmission and developed climate-based forecasting models for HFRS in northeastern China. ---------- Methods: We obtained data on monthly counts of reported HFRS cases in Elunchun and Molidawahaner counties for 1997–2007 from the Inner Mongolia Center for Disease Control and Prevention and climate data from the Chinese Bureau of Meteorology. Cross-correlations assessed crude associations between climate variables, including rainfall, land surface temperature (LST), relative humidity (RH), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI) and monthly HFRS cases over a range of lags. We used time-series Poisson regression models to examine the independent contribution of climatic variables to HFRS transmission. ----------- Results: Cross-correlation analyses showed that rainfall, LST, RH, and MEI were significantly associated with monthly HFRS cases with lags of 3–5 months in both study areas. The results of Poisson regression indicated that after controlling for the autocorrelation, seasonality, and long-term trend, rainfall, LST, RH, and MEI with lags of 3–5 months were associated with HFRS in both study areas. The final model had good accuracy in forecasting the occurrence of HFRS. ---------- Conclusions: Climate variability plays a significant role in HFRS transmission in northeastern China. The model developed in this study has implications for HFRS control and prevention.

Seasonal amplitude of hemorrhagic fever with renal syndrome in China : a call for attention to neglected regions

Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne viral disease characterized by fever, hemorrhagic, kidney damage and hypotension, is caused by different species of hantaviruses [1]. Every year, HFRS affects thousands of people in Asia, and more than 90% of these cases are reported in China [2, 3]. Due to its high fatality, HFRS has attracted considerable research attention, and prior studies have predominantly focused on quantifying HFRS morbidity [4], identifying high risk areas [5] and populations [6], or exploring peak time of HFRS occurrence [3]. To date, no study has assessed the seasonal amplitude of HFRS in China, even though it reveals the seasonal fluctuation and thus may provide pivotal information on the possibility of HFRS outbreaks.

Spatiotemporal transmission dynamics of hemorrhagic fever with renal syndrome in China, 2005-2012

Background Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by many serotypes of hantaviruses. In China, HFRS has been recognized as a severe public health problem with 90% of the total reported cases in the world. This study describes the spatiotemporal dynamics of HFRS cases in China and identifies the regions, time, and populations at highest risk, which could help the planning and implementation of key preventative measures. Methods Data on all reported HFRS cases at the county level from January 2005 to December 2012 were collected from Chinese Center for Disease Control and Prevention. Geographic Information System-based spatiotemporal analyses including Local Indicators of Spatial Association and Kulldorff's space-time scan statistic were performed to detect local high-risk space-time clusters of HFRS in China. In addition, cases from high-risk and low-risk counties were compared to identify significant demographic differences. Results A total of 100,868 cases were reported during 2005–2012 in mainland China. There were significant variations in the spatiotemporal dynamics of HFRS. HFRS cases occurred most frequently in June, November, and December. There was a significant positive spatial autocorrelation of HFRS incidence during the study periods, with Moran's I values ranging from 0.46 to 0.56 (P<0.05). Several distinct HFRS cluster areas were identified, mainly concentrated in northeastern, central, and eastern of China. Compared with cases from low-risk areas, a higher proportion of cases were younger, non-farmer, and floating residents in high-risk counties. Conclusions This study identified significant space-time clusters of HFRS in China during 2005–2012 indicating that preventative strategies for HFRS should be particularly focused on the northeastern, central, and eastern of China to achieve the most cost-effective outcomes.

Epidemiologic features of severe fever with Thrombocytopenia Syndrome in China, 2011-2012

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]...

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.

Risk factors for delayed healing in venous leg ulcers : a review of the literature

Background Chronic leg ulcers, remaining unhealed after 4–6 weeks, affect 1-3% of the population, with treatment costly and health service resource intensive. Venous disease contributes to approximately 70% of all chronic leg ulcers and these ulcers are often associated with pain, reduced mobility and a decreased quality of life. Despite evidence-based care, 30% of these ulcers are unlikely to heal within a 24-week period and therefore the recognition and identification of risk factors for delayed healing of venous leg ulcers would be beneficial. Aim To review the available evidence on risk factors for delayed healing of venous leg ulcers. Methods: A review of the literature in regard to risk factors for delayed healing in venous leg ulcers was conducted from January 2000 to December 2013. Evidence was sourced through searches of relevant databases and websites for resources addressing risk factors for delayed healing in venous leg ulcers specifically. Results Twenty-seven studies, of mostly low-level evidence (Level III and IV), identified risk factors associated with delayed healing. Risk factors that were consistently identified included: larger ulcer area, longer ulcer duration, a previous history of ulceration, venous abnormalities and lack of high compression. Additional potential predictors with inconsistent or varying evidence to support their influence on delayed healing of venous leg ulcers included decreased mobility and/or ankle range of movement, poor nutrition and increased age. Discussion Findings from this review indicate that a number of physiological risk factors are asso- ciated with delayed healing in venous leg ulcers and that social and/or psychological risk factors should also be considered and examined further. Conclusion The findings from this review can assist health professionals to identify prognostic indicators or risk factors significantly associated with delayed healing in venous leg ulcers. This will facilitate realistic outcome planning and inform implementation of appropriate early strategies to promote healing.

Risk factors associated with an outbreak of dengue fever/dengue haemorrhagic fever in Hanoi, Vietnam

Dengue fever/dengue haemorrhagic fever (DF/DHF) appears to be emerging in Hanoi in recent years. A case-control study was performed to investigate risk factors for the development of DF/DHF in Hanoi. A total of 73 patients with DF/DHF and 73 control patients were included in the study. The risk factor analysis indicated that living in rented housing, living near uncovered sewers, and living in a house discharging sewage directly into to ponds were all significantly associated with DF/DHF. People living in rented houses were 2·2 times more at risk of DF/DHF than those living in their own homes [adjusted odds ratio (aOR) 2·2, 95% confidence interval (CI) 1·1–4·6]. People living in an unhygienic house, or in a house discharging sewage directly to the ponds were 3·4 times and 4·3 times, respectively, more likely to be associated with DF/DHF (aOR 3·4, 95% CI 1–11·7; aOR 4·3, 95% CI 1·1–16·9). These results contribute to the understanding of the dynamics of dengue transmission in Hanoi, which is needed to implement dengue prevention and control programmes effectively and efficiently.

Increased risk of emergency hospital admissions for children with renal diseases during heatwaves in Brisbane, Australia

Background Heatwaves have a significant impact on population health including both morbidity and mortality. In this study we examined the association between heatwaves and emergency hospital admissions (EHAs) for renal diseases in children (aged 0–14 years) in Brisbane, Australia. Methods Daily data on EHAs for renal diseases in children and exposure to temperature and air pollution were obtained for Brisbane city from January 1, 1996 to December 31, 2005. A time-stratified case-crossover design was used to compare the risks for renal diseases between heatwave and non-heatwave periods. Results There were 1565 EHAs for renal diseases in children during the study period. Heatwaves exhibited a significant impact on EHAs for renal diseases in children after adjusting for confounding factors (odds ratio: 3.6; 95% confidence interval: 1.4–9.5). The risk estimates differed with lags and the use of different heatwave definitions. Conclusions There was a significant increase in EHAs for renal diseases in children during heatwaves in Brisbane, a subtropical city where people are well accustomed to warm weather. This finding may have significant implications for pediatric renal care, particularly in subtropical and tropical regions.

Risk factors for malnutrition in community-dwelling people with Parkinson’s disease

In the elderly, the risks for protein-energy malnutrition from older age, dementia, depression and living alone have been well-documented. Other risk factors including anorexia, gastrointestinal dysfunction, loss of olfactory and taste senses and early satiety have also been suggested to contribute to poor nutritional status. In Parkinson’s disease (PD), it has been suggested that the disease symptoms may predispose people with PD to malnutrition. However, the risks for malnutrition in this population are not well-understood. The current study’s aim was to determine malnutrition risk factors in community-dwelling adults with PD. Nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA). Data about age, time since diagnosis, medications and living situation were collected. Levodopa equivalent doses (LDED) and LDED per kg body weight (mg/kg) were calculated. Depression and anxiety were measured using the Beck’s Depression Inventory (BDI) and Spielberger Trait Anxiety questionnaire, respectively. Cognitive function was assessed using the Addenbrooke’s Cognitive Examination (ACE-R). Non-motor symptoms were assessed using the Scales for Outcomes in Parkinson's disease-Autonomic (SCOPA-AUT) and Modified Constipation Assessment Scale (MCAS). A total of 125 community-dwelling people with PD were included, average age of 70.2±9.3(35-92) years and average time since diagnosis of 7.3±5.9(0–31) years. Average body mass index (BMI) was 26.0±5.5kg/m2. Of these, 15% (n=19) were malnourished (SGA-B). Multivariate logistic regression analysis revealed that older age (OR=1.16, CI=1.02-1.31), more depressive symptoms (OR=1.26, CI=1.07-1.48), lower levels of anxiety (OR=.90, CI=.82-.99), and higher LDED per kg body weight (OR=1.57, CI=1.14-2.15) significantly increased malnutrition risk. Cognitive function, living situation, number of prescription medications, LDED, years since diagnosis and the severity of non-motor symptoms did not significantly influence malnutrition risk. Malnutrition results in poorer health outcomes. Proactively addressing the risk factors can help prevent declines in nutritional status. In the current study, older people with PD with depression and greater amounts of levodopa per body weight were at increased malnutrition risk.

Inflammation, hepatic enzymes and resistance training in individuals with metabolic risk factors

AIMS: Increases in inflammatory markers, hepatic enzymes and physical inactivity are associated with the development of the metabolic syndrome (MetS). We examined whether inflammatory markers and hepatic enzymes are correlated with traditional risk factors for MetS and studied the effects of resistance training (RT) on these emerging risk factors in individuals with a high number of metabolic risk factors (HiMF, 2.9 +/- 0.8) and those with a low number of metabolic risk factors (LoMF, 0.5 +/- 0.5). METHODS: Twenty-eight men and 27 women aged 50.8 +/- 6.5 years (mean +/- sd) participated in the study. Participants were randomized to four groups, HiMF training (HiMFT), HiMF control (HiMFC), LoMF training (LoMFT) and LoMF control (LoMFC). Before and after 10 weeks of RT [3 days/week, seven exercises, three sets with intensity gradually increased from 40-50% of one repetition maximum (1RM) to 75-85% of 1RM], blood samples were obtained for the measurement of pro-inflammatory cytokines, C-reactive protein (CRP), gamma-glutamyltransferase (GGT) and alanine aminotransferase (ALT). RESULTS: At baseline, HiMF had higher interleukin-6 (33.9%), CRP (57.1%), GGT (45.2%) and ALT (40.6%) levels, compared with LoMF (all P < 0.05). CRP, GGT and ALT correlated with the number of risk factors (r = 0.48, 0.51 and 0.57, respectively, all P < 0.01) and with other anthropometric and clinical measures (r range from 0.26 to 0.60, P < 0.05). RT did not significantly alter inflammatory markers or hepatic enzymes (all P > 0.05). CONCLUSIONS: HiMF was associated with increased inflammatory markers and hepatic enzyme concentrations. RT did not reduce inflammatory markers and hepatic enzymes in individuals with HiMF.

Risk factors for ocular surface squamous neoplasia recurrence after treatment with topical mitomycin C and interferon alpha-2b

Purpose To determine the rate of recurrence and associated risk factors following the use of mitomycin C (MMC) and/or interferon alpha-2b (IFN) for management of non-invasive ocular surface squamous neoplasia (OSSN). Design Retrospective non-comparative interventional case series. Methods Clinical practice setting of 135 patients treated consecutively with topical MMC (0.4 mg/mL) and/or IFN (1 million units/mL) for OSSN observed for clinical recurrence. Results Clinical recurrences were diagnosed in 19 of 135 (14.1%) eyes following topical treatment. The mean time to recurrence was 17.2 months (range 4 - 61) with 14 (73.7%) recurring within a two year period. There was no greater risk of recurrence identified for variables including lesion size, lesion location, gender, age, treatment type or duration. Post-hoc log-Rank pairwise comparisons revealed that lesions initially treated using surgery alone had significantly reduced time to recurrence (21.1 ± 5.6 months) compared to previous topical treatment with MMC (with or without surgery) (29.6 ± 4.7 months) (p = 0.04) and primary OSSN (23.2 ± 1.8 months) (p = 0.09). Conclusions Topical MMC and IFN are an effective treatment modality for a wide range of non-invasive OSSN. Topical therapy avoids the morbidity of excisional surgery with equivalent or reduced recurrence rates and should be considered as primary therapy.

Risk factors associated with corneal nerve alteration in type 1 diabetes in the absence of neuropathy: A longitudinal in vivo corneal confocal microscopy study

Purpose The aim of this study was to determine alterations to the corneal subbasal nerve plexus (SNP) over four years using in vivo corneal confocal microscopy (IVCM) in participants with type 1 diabetes and to identify significant risk factors associated with these alterations. Methods A cohort of 108 individuals with type 1 diabetes and no evidence of peripheral neuropathy at enrollment underwent laser-scanning IVCM, ocular screening, and health and metabolic assessment at baseline and the examinations continued for four subsequent annual visits. At each annual visit, eight central corneal images of the SNP were selected and analyzed to quantify corneal nerve fiber density (CNFD), branch density (CNBD) and fiber length (CNFL). Linear mixed model approaches were fitted to examine the relationship between risk factors and corneal nerve parameters. Results A total of 96 participants completed the final visit and 91 participants completed all visits. No significant relationships were found between corneal nerve parameters and time, sex, duration of diabetes, smoking, alcohol consumption, blood pressure or BMI. However, CNFD was negatively associated with HbA1c (β=-0.76, P<0.01) and age (β=-0.13, P<0.01) and positively related to high density lipids (HDL) (β=2.01, P=0.03). Higher HbA1c (β=-1.58, P=0.04) and age (β=-0.23, P<0.01) also negatively impacted CNBD. CNFL was only affected by higher age (β=-0.06, P<0.01). Conclusions Glycemic control, HDL and age have significant effects on SNP structure. These findings highlight the importance of diabetic management to prevent corneal nerve damage as well as the capability of IVCM for monitoring subclinical alterations in the corneal SNP in diabetes.