An integrated modeling and risk analysis tool for mine water interactions

Poor mine water management can lead to corporate, environmental and social risks. These risks become more pronounced as mining operations move into areas of water scarcity and/or increase climatic variability while also managing increased demand, lower ore grades and increased strip ratios. Therefore, it is vital that mine sites better understand these risks in order to implement management practices to address them. Systems models provide an effective approach to understand complex networks, particularly across multiple scales. Previous work has represented mine water interactions using systems model on a mine site scale. Here, we expand on that work by present an integrated tool that uses a systems modeling approach to represent mine water interactions on a site and regional scale and then analyses the risks associated with events stemming from those interactions. A case study is presented to represent three indicative corporate, environmental and social risks associated with a mine site that exists in a water scarce region. The tool is generic and flexible, and can be used in many scenarios to provide significant potential utility to the mining industry.

Community engagement for disaster resilience : flood risk management in Jakarta, Indonesia

Understanding dynamics of interactions between community groups and government agencies is crucial to improve community resilience for flood risk reduction through effective community engagement strategies. Overall, a variety of approaches are available, however they are limited in their application. Based on research of a case study in Kampung Melayu Village in Jakarta, further complexity in engaging community emerges in planning policy which requires the relocation of households living in floodplains. This complexity arises in decision-making processes due to barriers to communication. This obstacle highlights the need for a simplified approach for an effective flood risk management which will be further explored in this paper. Qualitative analyses will be undertaken following semi-structured interviews conducted with key actors within government agencies, non-governmental organisations (NGOs), and representatives of communities. The analyses involve investigation of barriers and constraints on community engagement in flood risk management, particularly relevant to collaboration mechanism, perception of risk, and technical literacy to flood risk. These analyses result in potential redirection of community consultation strategies to lead to a more effective collaboration among stakeholders in the decision-making processes. As a result, greater effectiveness in plan implementation of flood risk management potentially improves disaster resilience in the future.

Spatial analysis of risk factors for transmission of the Barmah forest virus in Queensland, Australia

Barmah Forest virus (BFV) disease is the second most common mosquito-borne disease in Australia but few data are available on the risk factors. We assessed the impact of spatial climatic, socioeconomic and ecological factors on the transmission of BFV disease in Queensland, Australia, using spatial regression. All our analyses indicate that spatial lag models provide a superior fit to the data compared to spatial error and ordinary least square models. The residuals of the spatial lag models were found to be uncorrelated, indicating that the models adequately account for spatial and temporal autocorrelation. Our results revealed that minimum temperature, distance from coast and low tide were negatively and rainfall was positively associated with BFV disease in coastal areas, whereas minimum temperature and high tide were negatively and rainfall was positively associated with BFV disease (all P-value.

Activity patterns of preschool-aged children at risk for obesity

BACKGROUND Although the prevalence of obesity in young children highlights the importance of early interventions to promote physical activity (PA), there are limited data on activity patterns in this age group. The purpose of this study is to describe activity patterns in preschool-aged children and explore differences by weight status. METHODS Analyses use baseline data from Healthy Homes/Healthy Kids- Preschool, a pilot obesity prevention trial of preschool-aged children overweight or at risk for overweight. A modified parent-reported version of the previous-day PA recall was used to summarize types of activity. Accelerometry was used to summarize daily and hourly activity patterns. RESULTS "Playing with toys" accounted for the largest proportion of a child's previous day, followed by "meals and snacks", and "chores". Accelerometry-measured daily time spent in sedentary behavior, light PA, and moderate-to-vigorous PA (MVPA) was 412, 247, and 69 minutes, respectively. Percent of hourly time spent in MVPA ranged from 3% to 13%, peaking in the late morning and evening hours. There were no statistically significant MVPA differences by weight status. CONCLUSIONS This study extends our understanding of activity types, amounts, and patterns in preschool-age children and warrants further exploration of differences in physical activity patterns by weight status.

Prevalence of active foot disease and foot disease risk factors in a subacute inpatient rehabilitation facility: a cross-sectional prevalence study

Background Australian subacute inpatient rehabilitation facilities face significant challenges from the ageing population and the increasing burden of chronic disease. Foot disease complications are a negative consequence of many chronic diseases. With the rapid expansion of subacute rehabilitation inpatient services, it seems imperative to investigate the prevalence of foot disease and foot disease risk factors in this population. The primary aim of this cross-sectional study was to determine the prevalence of active foot disease and foot disease risk factors in a subacute inpatient rehabilitation facility. Methods Eligible participants were all adults admitted at least overnight into a large Australian subacute inpatient rehabilitation facility over two different four week periods. Consenting participants underwent a short non-invasive foot examination by a podiatrist utilising the validated Queensland Health High Risk Foot Form to collect data on age, sex, medical co-morbidity history, foot disease risk factor history and clinically diagnosed foot disease complications and foot disease risk factors. Descriptive statistics were used to determine the prevalence of clinically diagnosed foot disease complications, foot disease risk factors and groups of foot disease risk factors. Logistic regression analyses were used to investigate any associations between defined explanatory variables and appropriate foot disease outcome variables. Results Overall, 85 (88%) of 97 people admitted to the facility during the study periods consented; mean age 80 (±9) years and 71% were female. The prevalence (95% confidence interval) of participants with active foot disease was 11.8% (6.3 – 20.5), 32.9% (23.9 – 43.5) had multiple foot disease risk factors, and overall, 56.5% (45.9 – 66.5) had at least one foot disease risk factor. A self-reported history of peripheral neuropathy diagnosis was independently associated with having multiple foot disease risk factors (OR 13.504, p = 0.001). Conclusion This study highlights the potential significance of the burden of foot disease in subacute inpatient rehabilitation facilities. One in eight subacute inpatients were admitted with active foot disease and one in two with at least one foot disease risk factor in this study. It is recommended that further multi-site studies and management guidelines are required to address the foot disease burden in subacute inpatient rehabilitation facilities. Keywords: Subacute; Inpatient; Foot; Complication; Prevalence

Lifecycle optimization and tradeoff analysis among competing objectives for a road corridor

While the philosophical motivation behind Civil Infrastructure Management Systems is to achieve optimal level of service at a minimum cost, the allocation of scarce resources among competing alternatives is still a matter of debate. It appears to be widely accepted that results from tradeoff analysis can be measured by the degree of accomplishment of the objectives. Road management systems not only deal with different asset types but also with conflicting objectives. This paper presents a case study of lifecycle optimization with tradeoff analysis for a road corridor in New Brunswick. Objectives of the study included condition of bridge and roads and road safety. A road safety index was created based on potential for improvement. Road condition was based on roughness, rutting and cracking. Initial results show lack of sustainability in bridge performance. Therefore, bridges where broken by components: deck, superstructure and substructure. Visual inspections, in addition to construction age of each bridge, were combined to generate a surrogate apparent age. Two life cycle analysis were conducted; one aimed to minimize overall cost while achieving sustainable results and another one purely for optimization. -used to identify required levels of budget. Such analyses were used to identify the minimum required budget and to demonstrate that with the same amount of money it was possible to achieve better levels of performance. Dominance and performance driven criteria were combined to identify and select an optimal result. It was found that achievement of optimally sustained results is conditioned by the availability of treatments for all asset classes at across their life spans. For the case study a disaggregated bridge condition index was introduced to the original algorithm to attempt to achieve sustainability in all bridges components, however lack of early stage treatments for substructures produce declining trends for such a component.

Do twins differ from single-born children on rates of behavioral difficulty in early childhood? A study of sibling relationship risk factors

The hypothesis that twinning raises risk for behavioral difficulties in childhood is persistent, yet there is limited and inconsistent empirical evidence. Simple mean comparison without control for confounders provides data on prevalence rates but cannot provide knowledge about risk or etiology. To assess the effect of twin relationship on behavior, comparison of patterns of association with single-born siblings may be informative. Analyses of data from an Australian sample of twins and single-born children (N = 305, mean age 4 years 9 months, and a follow-up 12 months later) were undertaken. The outcome measure was the Strengths and Difficulties Questionnaire. Predictor and control measures were obtained from parent report on the sibling/co-twin relationship behavior, family demographics, and obstetric history. We assessed difference between twins and single-born children in two respects: (a) mean behavioral difficulties, and (b) patterns of association between sibling relationship and behavioral difficulties, controlling for confounders. Results showed no differences in mean levels of behavioral difficulties between twins and single-born siblings identifying the importance of statistical control for family and obstetric adversity. Differences in patterns of association were found; for twin children, conflict in their co-twin relationship predicted externalizing behaviors, while for single-born children conflict predicted internalizing behaviors. The findings of mean differences between twin and single-born children in social background, but not in behavioral difficulties, underscore the necessity of statistical control to identify risk associated with twinning compared with risk associated with family and obstetric background factors.

Estimating the burden of disease attributable to four selected environmental risk factors in South Africa

INTRODUCTION: The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure. METHODS: The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty. RESULTS: Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease. CONCLUSION: This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence-based policies and programs must be developed and implemented to address these risk factors at individual, household, and community levels.

Extinction risk in cloud forest fragments under climate change and habitat loss

Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.

Psychological health and the risk of diabetes mellitus in Australian women: A 21-year prospective study

Background Symptoms of depression can be recurrent or limited to one episode. This study discusses the prospective association between psychological health, measured as change in depression symptoms, and the risk of diabetes mellitus in Australian women. Methods Data obtained from the Mater-University of Queensland Study of Pregnancy. Depression was measured using the Delusions-Symptoms: States Inventory. To examine possible transitions over time, depression was grouped into four categories and assessed at different phases over the 21-year period. Multiple logistic regression models and sensitivity analysis to assess the robustness of our analytical strategy were performed. Results Three hundred and one women reported diabetes 21 years after the index pregnancy. Almost one-third of the women who reported depression symptoms continued to report these at a subsequent follow-up (FU) phase. About 1 in 20 women who had not reported depression symptoms at the 5-year FU did so at the subsequent 14-year FU. In prospective analyses, we did not find a significant association between diabetes and negative change (not depressed to depressed, at subsequent phase); however, for women with positive history of symptoms of depression and women with persistent symptoms, there was a 1.97-fold (95% confidence interval [CI]: 1.14–3.40) to 2.23-fold (95% CI: 1.09–4.57) greater risk of diabetes. Conclusions Our study suggests that an increased risk of diabetes is significantly associated with persistent depression symptoms. It highlights the importance of recognizing depression symptoms in terms of women's psychological wellbeing and thus provides a basis for targeting those most at risk.

Inferring lung cancer risk factor patterns through joint Bayesian spatio-temporal analysis

Background: Preventing risk factor exposure is vital to reduce the high burden from lung cancer. The leading risk factor for developing lung cancer is tobacco smoking. In Australia, despite apparent success in reducing smoking prevalence, there is limited information on small area patterns and small area temporal trends. We sought to estimate spatio-temporal patterns for lung cancer risk factors using routinely collected population-based cancer data. Methods: The analysis used a Bayesian shared component spatio-temporal model, with male and female lung cancer included separately. The shared component reflected exposure to lung cancer risk factors, and was modelled over 477 statistical local areas (SLAs) and 15 years in Queensland, Australia. Analyses were also run adjusting for area-level socioeconomic disadvantage, Indigenous population composition, or remoteness. Results: Strong spatial patterns were observed in the underlying risk factor exposure for both males (median Relative Risk (RR) across SLAs compared to the Queensland average ranged from 0.48-2.00) and females (median RR range across SLAs 0.53-1.80), with high exposure observed in many remote areas. Strong temporal trends were also observed. Males showed a decrease in the underlying risk across time, while females showed an increase followed by a decrease in the final two years. These patterns were largely consistent across each SLA. The high underlying risk estimates observed among disadvantaged, remote and indigenous areas decreased after adjustment, particularly among females. Conclusion: The modelled underlying exposure appeared to reflect previous smoking prevalence, with a lag period of around 30 years, consistent with the time taken to develop lung cancer. The consistent temporal trends in lung cancer risk factors across small areas support the hypothesis that past interventions have been equally effective across the state. However, this also means that spatial inequalities have remained unaddressed, highlighting the potential for future interventions, particularly among remote areas.

Refining prognosis and identifying targetable pathways for high-risk endometrial cancer; a TransPORTEC initiative

This study aimed to investigate whether molecular analysis can be used to refine risk assessment, direct adjuvant therapy, and identify actionable alterations in high-risk endometrial cancer. TransPORTEC, an international consortium related to the PORTEC3 trial, was established for translational research in high-risk endometrial cancer. In this explorative study, routine molecular analyses were used to detect prognostic subgroups: p53 immunohistochemistry, microsatellite instability and POLE proofreading mutation. Furthermore, DNA was analyzed for hotspot mutations in 13 additional genes (BRAF, CDKNA2, CTNNB1, FBXW7, FGFR2, FGFR3, FOXL2, HRAS, KRAS, NRAS, PIK3CA, PPP2R1A, and PTEN) and protein expression of ER, PR, PTEN, and ARID1a was analyzed. Rates of distant metastasis, recurrence-free, and overall survival were calculated using the Kaplan-Meier method and log-rank test. In total, samples of 116 high-risk endometrial cancer patients were included: 86 endometrioid; 12 serous; and 18 clear cell. For endometrioid, serous, and clear cell cancers, 5-year recurrence-free survival rates were 68%, 27%, and 50% (P=0.014) and distant metastasis rates 23%, 64%, and 50% (P=0.001), respectively. Four prognostic subgroups were identified: (1) a group of p53-mutant tumors; (2) microsatellite instable tumors; (3) POLE proofreading-mutant tumors; and (4) a group with no specific molecular profile (NSMP). In group 3 (POLE-mutant; n=14) and group 2 (microsatellite instable; n=19) patients, no distant metastasis occurred, compared with 50% distant metastasis rate in group 1 (p53-mutant; n=36) and 39% in group 4 (NSMP; P<0.001). Five-year recurrence-free survival was 93% and 95% for group 3 (POLE-mutant) and group 2 (microsatellite instable) vs 42% (group 1, p53-mutant) and 52% (group 4, NSMP; P<0.001). Targetable FBXW7 and FGFR2 mutations (6%), alterations in the PI3K-AKT pathway (60%) and hormone receptor positivity (45%) were frequently found. In conclusion, molecular analysis of high-risk endometrial cancer identifies four distinct prognostic subgroups, with potential therapeutic implications. High frequencies of targetable alterations were identified and may serve as targets for individualized treatment

Saudi Arabian adult intensive care unit pressure ulcer incidence and risk factors: A prospective cohort study

The purpose of this study was to identify pressure ulcer (PU) incidence and risk factors that are associated with PU development in patients in two adult intensive care units (ICU) in Saudi Arabia. A prospective cohort study design was used. A total of 84 participants were screened second daily basis until discharge or death, over a consecutive 30-day period, out of which 33 participants with new PUs were identified giving a cumulative hospital-acquired PU incidence of 39·3% (33/84 participants). The incidence of medical devices-related PUs was 8·3% (7/84). Age, length of stay in the ICU, history of cardiovascular disease and kidney disease, infrequent repositioning, time of operation, emergency admission, mechanical ventilation and lower Braden Scale scores independently predicted the development of a PU. According to binary logistic regression analyses, age, longer stay in ICU and infrequent repositioning were significant predictors of all stages of PUs, while the length of stay in the ICU and infrequent repositioning were associated with the development of stages II-IV PUs. In conclusion, PU incidence rate was higher than that reported in other international studies. This indicates that urgent attention is required for PU prevention strategies in this setting.

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10−14, odds ratio = 0.86, 95% confidence interval = 0.82–0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression.

Genetic risk score analysis indicates migraine with and without comorbid depression are genetically different disorders

Migraine and major depressive disorder (MDD) are comorbid, moderately heritable and to some extent influenced by the same genes. In a previous paper, we suggested the possibility of causality (one trait causing the other) underlying this comorbidity. We present a new application of polygenic (genetic risk) score analysis to investigate the mechanisms underlying the genetic overlap of migraine and MDD. Genetic risk scores were constructed based on data from two discovery samples in which genome-wide association analyses (GWA) were performed for migraine and MDD, respectively. The Australian Twin Migraine GWA study (N = 6,350) included 2,825 migraine cases and 3,525 controls, 805 of whom met the diagnostic criteria for MDD. The RADIANT GWA study (N = 3,230) included 1,636 MDD cases and 1,594 controls. Genetic risk scores for migraine and for MDD were used to predict pure and comorbid forms of migraine and MDD in an independent Dutch target sample (NTR-NESDA, N = 2,966), which included 1,476 MDD cases and 1,058 migraine cases (723 of these individuals had both disorders concurrently). The observed patterns of prediction suggest that the 'pure' forms of migraine and MDD are genetically distinct disorders. The subgroup of individuals with comorbid MDD and migraine were genetically most similar to MDD patients. These results indicate that in at least a subset of migraine patients with MDD, migraine may be a symptom or consequence of MDD. © 2013 Springer-Verlag Berlin Heidelberg.