Analysis of longitudinal data in the presence of informative observational times and a dependent terminal event, with application to medical cost data

Summary .   In longitudinal observational studies, repeated measures are often taken at informative observation times. Also, there may exist a dependent terminal event such as death that stops the follow-up. For example, patients in poorer health are more likely to seek medical treatment and their medical cost for each visit tends to be higher. They are also subject to a higher mortality rate. In this article, we propose a random effects model of repeated measures in the presence of both informative observation times and a dependent terminal event. Three submodels are used, respectively, for (1) the intensity of recurrent observation times, (2) the amount of repeated measure at each observation time, and (3) the hazard of death. Correlated random effects are incorporated to join the three submodels. The estimation can be conveniently accomplished by Gaussian quadrature techniques, e.g., SAS Proc NLMIXED . An analysis of the cost-accrual process of chronic heart failure patients from the clinical data repository at the University of Virginia Health System is presented to illustrate the proposed method.     

Opportunities for renewable bioenergy using microorganisms

Global warming can be slowed, and perhaps reversed, only when society replaces fossil fuels with renewable, carbon-neutral alternatives. The best option is bioenergy: the sun's energy is captured in biomass and converted to energy forms useful to modern society. To make a dent in global warming, bioenergy must be generated at a very high rate, since the world today uses approximately 10 TW of fossil-fuel energy. And, it must do so without inflicting serious damage on the environment or disrupting our food supply. While most bioenergy options fail on both counts, several microorganism-based options have the potential to produce large amounts of renewable energy without disruptions. In one approach, microbial communities convert the energy value of various biomass residuals to socially useful energy. Biomass residuals come from agricultural, animal, and a variety of industrial operations, as well as from human wastes. Microorganisms can convert almost all of the energy in these wastes to methane, hydrogen, and electricity. In a second approach, photosynthetic microorganisms convert sunlight into biodiesel. Certain algae (eukaryotes) or cyanobacteria (prokaryotes) have high lipid contents. Under proper conditions, these photosynthetic microorganisms can produce lipids for biodiesel with yields per unit area 100 times or more than possible with any plant system. In addition, the non-lipid biomass can be converted to methane, hydrogen, or electricity. Photosynthetic microorganisms do not require arable land, an advantage because our arable land must be used to produce food. Algae or cyanobacteria may be the best option to produce bioenergy at rates high enough to replace a substantial fraction of our society's use of fossil fuels.     

Analysis of ammonia loss mechanisms in microbial fuel cells treating animal wastewater

Ammonia losses during swine wastewater treatment were examined using single- and two-chambered microbial fuel cells (MFCs). Ammonia removal was 60% over 5 days for a single-chamber MFC with the cathode exposed to air (air-cathode), versus 69% over 13 days from the anode chamber in a two-chamber MFC with a ferricyanide catholyte. In both types of systems, ammonia losses were accelerated with electricity generation. For the air-cathode system, our results suggest that nitrogen losses during electricity generation were increased due to ammonia volatilization with conversion of ammonium ion to the more volatile ammonia species as a result of an elevated pH near the cathode (where protons are consumed). This loss mechanism was supported by abiotic tests (applied voltage of 1.1 V). In a two-chamber MFC, nitrogen losses were primarily due to ammonium ion diffusion through the membrane connecting the anode and cathode chambers. This loss was higher with electricity generation as the rate of ammonium transport was increased by charge transfer across the membrane. Ammonia was not found to be used as a substrate for electricity generation, as intermittent ammonia injections did not produce power. The ammonia-oxidizing bacterium Nitrosomonas europaea was found on the cathode electrode of the single-chamber system, supporting evidence of biological nitrification, but anaerobic ammonia-oxidizing bacteria were not detected by molecular analyses. It is concluded that ammonia losses from the anode chamber were driven primarily by physical-chemical factors that are increased with electricity generation, although some losses may occur through biological nitrification and denitrification.     

Weight-of-Evidence (WOE): Quantitative Estimation of Probability of Impairment for Individual and Multiple Lines of Evidence

Environmental decision-making is complex and often based on multiple lines of evidence. Integrating the information from these multiple lines of evidence is rarely a simple process. We present a quantitative approach to the combination of multiple lines of evidence through calculation of weight-of-evidence, with reference conditions used to define a not impaired state. The approach is risk-based with measurement of risk computed as the probability of impairment. When data on reference conditions are available, there are a variety of methods for calculating this probability. Statistical theory and the use of odds ratios provide a method for combining the measures of risk from the different lines of evidence. The approach is illustrated using data from the Great Lakes to predict the risk at potentially contaminated sites.     

Tree growth in the aftermath of A flood: A tree-ring based reconstruction of the impacts of the 1996-Biescas catastrophe

Catastrophic floods and large debris flows are natural hazards common in mountain areas. They cause injuries and impact the radial growth of trees growing in the affected basins. Reconstructing how these catastrophic events impact trees by using dendrochronology improves our understanding of natural hazards. The 1996-Biescas (Central Spanish Pyrenees) flood was a catastrophic event causing the loss of many lives in a campsite located on an active alluvial fan. We investigated using tree rings how this catastrophic flood impacted planted trees (poplars, cedars) located in the campsite. Conspicuous scars in the stem were more abundant in cedar trees (75 %) than in poplar (36 %) trees. Scarred cedar trees formed traumatic resin ducts after the flood. In cedar tree perimeter influenced the size of the wound formed after the flood, but this was not observed in poplar. On average, 63 % of trees showing scars formed them in the side of the stem (N-NW) where the impact of the flood was assumed to be strongest. We also detected sharp reductions of tree-ring width after the flood (–56 % and –16 % in poplar and cedar, respectively). However, this was not found when using basal area increment, which suggests there was an age effect on the post-flood growth changes. The two species mean chronologies were also more coupled after the flood in agreement with an increased responsiveness to climate, particularly a higher dependence of growth on June precipitation. To adequately reconstruct responses to flood and to assess the actual vulnerability of forests to debris flow impacts tree features such as species, age, growth rate and responsiveness to climate must be considered.     

Parametric and Parametrically Smoothed Distribution-Free Proportional Hazard Models with Discrete Data

This paper discusses discrete time proportional hazard models and suggests a new class of flexible hazard functions. Explicitly modeling the discreteness of data is important since standard continuous models are biased; allowing for flexibility in the hazard estimation is desirable since strong parametric restrictions are likely to be similarly misleading. Simulation compare continuous and discrete models when data are generated by grouping and demonstrate that simple approximations recover underlying hazards well and outperform nonparametric maximum likelihood estimates in term of mean squared error.     

Health risk assessment via consumption of Pb and Cd contaminated vegetables collected from fresh markets in the lower north of Thailand

This study aimed to investigate the Pb and Cd contamination and health risk assessment for population via consumption of vegetables sold in fresh markets around the lower north of Thailand. The concentrations of Pb and Cd in various vegetables such as root/tuber, stem, inflorescence, fruit, and leaf vegetables were analyzed using an atomic absorption spec-trophotometer. Human health risks of these metals in vegetables were assessed based on target hazard quotient (THQ). The results indicated that more than 80% of the Pb and Cd in almost all vegetable samples exceeded the maximum allowable concentration by National Food Institute criteria with an average range of 0.96–3.39 and 0.48–1.40 mg/kg, respectively. The estimated daily intakes (EDI) of Pb and Cd via dietary consumption of vegetables were between 0.001–0.010 and 0.002–0.008 mg/kg/d, respectively. All EDIs of Pb contaminated vegetables were higher than the reference dose recommended by the USEPA except for leaf edible vegetables, while all EDIs of Cd contaminated vegetables were higher than the reference dose recommended by the USEPA. THQ indicated that the consumption of Pb contaminated root/tuber, stem, inflorescence, and fruit edible vegetables and Cd contaminated leaf vegetable for the local population in the lower north of Thailand could be a severe health risk problem.     

Contamination level and human health hazard assessment of heavy metals and polycyclic aromatic hydrocarbons (PAHs) in street dust deposited in Mahshahr,southwest of Iran

Mahshahr has a strategic position and is considered as industrial hub of Iran. Selected heavy metals and polycyclic aromatic hydrocarbons (PAHs) contamination and health risk, and the mineralogical composition of street dust from Mahshahr were investigated. Results indicated that geology is the main determinant of the dust mineralogical composition. Calculated enrichment factor (EF) and principal component analysis (PCA) showed that Pb, Hg, Zn, and Cu accumulations are greatly influenced by anthropogenic sources including traffic and industry. High heavy metals content poses great ecological risk in the study area and exposure doses revealed that ingestion is the main exposure route to street dust, especially for children in residential/commercial areas. It was found that the total amount of PAHs (∑PAHs) varies from 161 to 1996 µg/kg, dominated by four-ring PAHs. Diagnostic ratios and PCA showed that both petrogenic and pyrogenic sources of PAHs in Mahshahr street dust and traffic play important roles in this respect. Furthermore, toxic equivalents and incremental lifetime cancer risk of PAHs in street dust indicated a high potential carcinogenic risk for inhabitants mainly via dermal contact and ingestion pathways particularly for outdoor workers in industrial use scenario. Finally, distribution maps of total hazard index of heavy metals and cancer risk of PAHs indicated the most impacted zones for different groups and use scenarios.