Evaluation of protein bait laced with various insecticides on the Queensland fruit fly (Diptera: Tephritidae): Attraction, feeding, mortality and bait persistence

The use of malathion in fruit fly protein bait sprays has raised serious concerns due to its adverse effects on non-target organisms. This has necessitated the evaluation of novel reduced-risk compounds. This study evaluated the effects of spinosad, fipronil, malathion and chlorpyrifos mixed with fruit fly protein bait (Mauri Pinnacle protein®) on attraction, feeding and mortality of the Queensland fruit fly, Bactrocera tryoni (Froggatt). The effects of outdoor weathering of these mixtures on fly mortality were also determined. In field-cage experiment, protein-starved flies showed the same level of attraction to baits containing spinosad, fipronil, malathion, chlorpyrifos and protein alone used as control. Female protein-starved flies were deterred from feeding on baits containing malathion and chlorpyrifos compared to baits containing spinosad, fipronil and protein alone. Baits containing malathion and chlorpyrifos caused higher fly mortality and rapid fly knock down than spinosad and fipronil. However, spinosad acted slowly and caused an increase in fly mortality over time, causing up to 90% fly mortality after 72-h. Baits containing malathion and chlorpyrifos, applied on citrus leaves and weathered outdoors, had longer residual effectiveness in killing flies than spinosad and fipronil. Residual effectiveness of the spinosad bait mixture waned significantly after 3 days of outdoor weathering. Results suggest that spinosad and fipronil can be potential alternatives for malathion in protein bait sprays.

Global variation in the effects of ambient temperature on mortality: A systematic evaluation

Background: Studies have examined the effects of temperature on mortality in a single city, country, or region. However, less evidence is available on the variation in the associations between temperature and mortality in multiple countries, analyzed simultaneously. Methods: We obtained daily data on temperature and mortality in 306 communities from 12 countries/regions (Australia, Brazil, Thailand, China, Taiwan, Korea, Japan, Italy, Spain, United Kingdom, United States, and Canada). Two-stage analyses were used to assess the nonlinear and delayed relation between temperature and mortality. In the first stage, a Poisson regression allowing overdispersion with distributed lag nonlinear model was used to estimate the community-specific temperature-mortality relation. In the second stage, a multivariate meta-analysis was used to pool the nonlinear and delayed effects of ambient temperature at the national level, in each country. Results: The temperatures associated with the lowest mortality were around the 75th percentile of temperature in all the countries/regions, ranging from 66th (Taiwan) to 80th (UK) percentiles. The estimated effects of cold and hot temperatures on mortality varied by community and country. Meta-analysis results show that both cold and hot temperatures increased the risk of mortality in all the countries/regions. Cold effects were delayed and lasted for many days, whereas heat effects appeared quickly and did not last long. Conclusions: People have some ability to adapt to their local climate type, but both cold and hot temperatures are still associated with increased risk of mortality. Public health strategies to alleviate the impact of ambient temperatures are important, in particular in the context of climate change.

Temperature variation between neighboring days and mortality: a distributed lag non-linear analysis

Objectives To investigate whether a sudden temperature change between neighboring days has significant impact on mortality. Methods A Poisson generalized linear regression model combined with a distributed lag non-linear models was used to estimate the association of temperature change between neighboring days with mortality in a subtropical Chinese city during 2008–2012. Temperature change was calculated as the current day’s temperature minus the previous day’s temperature. Results A significant effect of temperature change between neighboring days on mortality was observed. Temperature increase was significantly associated with elevated mortality from non-accidental and cardiovascular diseases, while temperature decrease had a protective effect on non-accidental mortality and cardiovascular mortality. Males and people aged 65 years or older appeared to be more vulnerable to the impact of temperature change. Conclusions Temperature increase between neighboring days has a significant adverse impact on mortality. Further health mitigation strategies as a response to climate change should take into account temperature variation between neighboring days.

Mortality reduction following the air pollution control measures during the 2010 Asian Games

Though increased particulate air pollution has been consistently associated with elevated mortality, evidence regarding whether diminished particulate air pollution would lead to mortality reduction is limited. Citywide air pollution mitigation program during the 2010 Asian Games in Guangzhou, China, provided such an opportunity. Daily mortality from non-accidental, cardiovascular and respiratory diseases was compared for 51 intervention days (November 1–December 21) in 2010 with the same calendar date of baseline years (2006–2009 and 2011). Relative risk (RR) and 95% confidence interval (95% CI) were estimated using a time series Poisson model, adjusting for day of week, public holidays, daily mean temperature and relative humidity. Daily PM10 (particle with aerodynamic diameter less than 10 μm) decreased from 88.64 μg/m3 during the baseline period to 80.61 μg/m3 during the Asian Games period. Other measured air pollutants and weather variables did not differ substantially. Daily mortality from non-accidental, cardiovascular and respiratory diseases decreased from 32, 11 and 6 during the baseline period to 25, 8 and 5 during the Games period, the corresponding RR for the Games period compared with the baseline period was 0.79 (95% CI: 0.73–0.86), 0.77 (95% CI: 0.66–0.89) and 0.68 (95% CI: 0.57–0.80), respectively. No significant decreases were observed in other months of 2010 in Guangzhou and intervention period in two control cities. This finding supports the efforts to reduce air pollution and improve public health through transportation restriction and industrial emission control.

Incidence and mortality of female breast cancer in the Asia-Pacific region

Objective: To provide an overview of the incidence and mortality of female breast cancer for countries in the Asia-Pacific region. Methods: Statistical information about breast cancer was obtained from publicly available cancer registry and mortality databases (such as GLOBOCAN), and supplemented with data requested from individual cancer registries. Rates were directly age-standardised to the Segi World Standard population and trends were analysed using joinpoint models. Results: Breast cancer was the most common type of cancer among females in the region, accounting for 18% of all cases in 2012, and was the fourth most common cause of cancer-related deaths (9%). Although incidence rates remain much higher in New Zealand and Australia, rapid rises in recent years were observed in several Asian countries. Large increases in breast cancer mortality rates also occurred in many areas, particularly Malaysia and Thailand, in contrast to stabilising trends in Hong Kong and Singapore, while decreases have been recorded in Australia and New Zealand. Mortality trends tended to be more favourable for women aged under 50 compared to those who were 50 years or older. Conclusion: It is anticipated that incidence rates of breast cancer in developing countries throughout the Asia-Pacific region will continue to increase. Early detection and access to optimal treatment are the keys to reducing breast cancer-related mortality, but cultural and economic obstacles persist. Consequently, the challenge is to customise breast cancer control initiatives to the particular needs of each country to ensure the best possible outcomes.

Impact of temperature on mortality in three major Chinese cities

To study the relation between temperature and mortality by estimating the temperature-related mortality in Beijing, Shanghai, and Guangzhou. METHODS: Data of daily mortality, weather and air pollution in the three cities were collected. A distributed lag nonlinear model was established and used in analyzing the effects of temperature on mortality. Current and future net temperature-related mortality was estimated. RESULTS: The association between temperature and mortality was J-shaped, with an increased death risk of both hot and cold temperature in these cities. The effects of cold temperature on health lasted longer than those of hot temperature. The projected temperature-related mortality increased with the decreased cold-related mortality. The mortality was higher in Guangzhou than in Beijing and Shanghai. CONCLUSION: The impact of temperature on health varies in the 3 cities of China, which may have implications for climate policy making in China.

The effects of ambient temperature on cerebrovascular mortality: An epidemiologic study in four climatic zones in China

Background Little evidence is available about the association between temperature and cerebrovascular mortality in China. This study aims to examine the effects of ambient temperature on cerebrovascular mortality in different climatic zones in China. Method We obtained daily data on weather conditions, air pollution and cerebrovascular deaths from five cities (Beijing, Tianjin, Shanghai, Wuhan, and Guangzhou) in China during 2004-2008. We examined city-specific associations between ambient temperature and the cerebrovascular mortality, while adjusting for season, long-term trends, day of the week, relative humidity and air pollution. We examined cold effects using a 1°C decrease in temperature below a city-specific threshold, and hot effects using a 1°C increase in temperature above a city-specific threshold. We used a meta-analysis to summarize the cold and hot effects across the five cities. Results Beijing and Tianjin (with low mean temperature) had lower thresholds than Shanghai, Wuhan and Guangzhou (with high mean temperature). In Beijing, Tianjin, Wuhan and Guangzhou cold effects were delayed, while in Shanghai there was no or short induction. Hot effects were acute in all five cities. The cold effects lasted longer than hot effects. The hot effects were followed by mortality displacement. The pooled relative risk associated with a 1°C decrease in temperature below thresholds (cold effect) was 1.037 (95% confidence interval (CI): 1.020, 1.053). The pooled relative risk associated with a 1°C increase in temperature above thresholds (hot effect) was 1.014 (95% CI: 0.979, 1.050). Conclusion Cold temperatures are significantly associated with cerebrovascular mortality in China, while hot effect is not significant. People in colder climate cities were sensitive to hot temperatures, while people in warmer climate cities were vulnerable to cold temperature.

Size-dependent natural mortality of juvenile banana prawns Penaeus merguiensis in the Gulf of Carpentaria, Australia

Natural mortality of marine invertebrates is often very high in the early life history stages and decreases in later stages. The possible size-dependent mortality of juvenile banana prawns, P. merguiensis (2-15 mm carapace length) in the Gulf of Carpentaria was investigated. The analysis was based on the data collected at 2-weekly intervals by beam trawls at four sites over a period of six years (between September 1986 and March 1992). It was assumed that mortality was a parametric function of size, rather than a constant. Another complication in estimating mortality for juvenile banana prawns is that a significant proportion of the population emigrates from the study area each year. This effect was accounted for by incorporating the size-frequency pattern of the emigrants in the analysis. Both the extra parameter in the model required to describe the size dependence of mortality, and that used to account for emigration were found to be significantly different from zero, and the instantaneous mortality rate declined from 0.89 week(-1) for 2 mm prawns to 0.02 week(-1) for 15 mm prawns.

Maximum likelihood estimation of mortality and growth with individual variability from multiple length-frequency data

We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L-infinity. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.

Population structure, mortality and growth of Pinna nobilis Linnaeus, 1758 (Mollusca, Bivalvia) at different depths in Moraira bay (Alicante, Western Mediterranean)

An investigation to characterize the causes of Pinna nobilis population structure in Moraira bay (Western Mediterranean) was developed. Individuals of two areas of the same Posidonia meadow, located at different depths (A1, -13 and A2, -6 m), were inventoried, tagged, their positions accurately recorded and monitored from July 1997 to July 2002. On each area, different aspects of population demography were studied (i.e. spatial distribution, size structure, displacement evidences, mortality, growth and shell orientation). A comparison between both groups of individuals was carried out, finding important differences between them. In A1, the individuals were more aggregated and mean and maximum size were higher (A1, 10.3 and A2, 6 individuals/100 m(2); A1, x = 47.2 +/- 9.9; A2, x = 29.8 +/- 7.4 cm, P < 0.001, respectively). In A2, growth rate and mortality were higher, the latter concentrated on the largest individuals, in contrast to A1, where the smallest individuals had the higher mortality rate [A1, L = 56.03(1 - e(-0.17t)); A2, L = 37.59(1 - e(-0.40t)), P < 0.001; mean annual mortality A1: 32 dead individuals out of 135, 23.7% and A2: 16 dead individuals out of 36, 44.4%, and total mortality coefficients (z), z(A1(-30)) = 0.28, z(A1(31-45)) = 0.05, z(A1(46-)) = 0.08; z(A2(-30)) = 0.15, z(A2(31-45)) = 0.25]. A common shell orientation N-S, coincident with the maximum shore exposure, was observed in A2. Spatial distribution in both areas showed not enough evidence to discard a random distribution of the individuals, despite the greater aggregation on the deeper area (A1) (A1, chi(2) = 0.41, df = 3, P > 0.5, A2, chi(2)= 0.98, df = 2 and 0.3 < P < 0.5). The obtained results have demonstrated that the depth-related size segregation usually shown by P. nobilis is mainly caused by differences in mortality and growth among individuals located at different depths, rather than by the active displacement of individuals previously reported in the literature. Furthermore, dwarf individuals are observed in shallower levels and as a consequence, the relationship between size and age are not comparable even among groups of individuals inhabiting the same meadow at different depths. The final causes of the differences on mortality and growth are also discussed.

A maximum-likelihood method for estimating natural mortality and catchability coefficient from catch-and-effort data

A simple stochastic model of a fish population subject to natural and fishing mortalities is described. The fishing effort is assumed to vary over different periods but to be constant within each period. A maximum-likelihood approach is developed for estimating natural mortality (M) and the catchability coefficient (q) simultaneously from catch-and-effort data. If there is not enough contrast in the data to provide reliable estimates of both M and q, as is often the case in practice, the method can be used to obtain the best possible values of q for a range of possible values of M. These techniques are illustrated with tiger prawn (Penaeus semisulcatus) data from the Northern Prawn Fishery of Australia.

Sitting-time and 9-year all-cause mortality in older women

Background Studies of mid-aged adults provide evidence of a relationship between sitting-time and all-cause mortality, but evidence in older adults is limited. The aim is to examine the relationship between total sitting-time and all-cause mortality in older women. Methods The prospective cohort design involved 6656 participants in the Australian Longitudinal Study on Women's Health who were followed for up to 9 years (2002, age 76–81, to 2011, age 85–90). Self-reported total sitting-time was linked to all-cause mortality data from the National Death Index from 2002 to 2011. Cox proportional hazard models were used to examine the relationship between sitting-time and all-cause mortality, with adjustment for potential sociodemographic, behavioural and health confounders. Results There were 2003 (30.1%) deaths during a median follow-up of 6 years. Compared with participants who sat <4 h/day, those who sat 8–11 h/day had a 1.45 times higher risk of death and those who sat ≥11 h/day had a 1.65 times higher risk of death. These risks remained after adding sociodemographic and behavioural covariates, but were attenuated after adjustment for health covariates. A significant interaction (p=0.02) was found between sitting-time and physical activity (PA), with increased mortality risk for prolonged sitting only among participants not meeting PA guidelines (HR for sitting ≥8 h/day: 1.31, 95% CI 1.07 to 1.61); HR for sitting ≥11 h/day: 1.47, CI 1.15 to 1.93). Conclusions Prolonged sitting-time was positively associated with all-cause mortality. Women who reported sitting for more than 8 h/day and did not meet PA guidelines had an increased risk of dying within the next 9 years.

Impact of malnutrition on 12-month mortality following acute hip fracture

Background Studies investigating the relationship between malnutrition and post-discharge mortality following acute hip fracture yield conflicting results. This study aimed to determine whether malnutrition independently predicted 12-month post-fracture mortality after adjusting for clinically relevant covariates. Methods An ethics approved, prospective, consecutive audit was undertaken for all surgically treated hip fracture inpatients admitted to a dedicated orthogeriatric unit (November 2010–October 2011). The 12-month mortality data were obtained by a dual search of the mortality registry and Queensland Health database. Malnutrition was evaluated using the Subjective Global Assessment. Demographic (age, gender, admission residence) and clinical covariates included fracture type, time to surgery, anaesthesia type, type of surgery, post-surgery time to mobilize and post-operative complications (delirium, pulmonary and deep vein thrombosis, cardiac complications, infections). The Charlson Comorbidity Index was retrospectively applied. All diagnoses were confirmed by the treating orthogeriatrician. Results A total of 322 of 346 patients were available for audit. Increased age (P = 0.004), admission from residential care (P < 0.001), Charlson Comorbidity Index (P = 0.007), malnutrition (P < 0.001), time to mobilize >48 h (P < 0.001), delirium (P = 0.003), pulmonary embolism (P = 0.029) and cardiovascular complication (P = 0.04) were associated with 12-month mortality. Logistic regression analysis demonstrated that malnutrition (odds ratio (OR) 2.4 (95% confidence interval (CI) 1.3–4.7, P = 0.007)), in addition to admission from residential care (OR 2.6 (95% CI 1.3–5.3, P = 0.005)) and pulmonary embolism (OR 11.0 (95% CI 1.5–78.7, P = 0.017)), independently predicted 12-month mortality. Conclusions Findings substantiate malnutrition as an independent predictor of 12-month mortality in a representative sample of hip fracture inpatients. Effective strategies to identify and treat malnutrition in hip fracture should be prioritized.

Early post-operative mortality after major lower limb amputation: A systematic review of population and regional based studies

OBJECTIVE: Lower limb amputation is often associated with a high risk of early post-operative mortality. Mortality rates are also increasingly being put forward as a possible benchmark for surgical performance. The primary aim of this systematic review is to investigate early post-operative mortality following a major lower limb amputation in population/regional based studies, and reported factors that might influence these mortality outcomes. METHODS: Embase, PubMed, Cinahl and Psycinfo were searched for publications in any language on 30 day or in hospital mortality after major lower limb amputation in population/regional based studies. PRISMA guidelines were followed. A self developed checklist was used to assess quality and susceptibility to bias. Summary data were extracted for the percentage of the population who died; pooling of quantitative results was not possible because of methodological differences between studies. RESULTS: Of the 9,082 publications identified, results were included from 21. The percentage of the population undergoing amputation who died within 30 days ranged from 7% to 22%, the in hospital equivalent was 4-20%. Transfemoral amputation and older age were found to have a higher proportion of early post-operative mortality, compared with transtibial and younger age, respectively. Other patient factors or surgical treatment choices related to increased early post-operative mortality varied between studies. CONCLUSIONS: Early post-operative mortality rates vary from 4% to 22%. There are very limited data presented for patient related factors (age, comorbidities) that influence mortality. Even less is known about factors related to surgical treatment choices, being limited to amputation level. More information is needed to allow comparison across studies or for any benchmarking of acceptable mortality rates. Agreement is needed on key factors to be reported.