Applying Health Locus of Control and Latent Class Modelling to food and physical activity choices affecting CVD risk

Health Locus of Control (HLC) classifies our beliefs about the connection between our actions and health outcomes (Skinner, 1996) into three categories: “internal control”, corresponding to health being the result of an individual's effort and habits; “control by powerful others”, whereby health depends on others, such as doctors; and “chance control”, according to which health depends on fate and chance. Using Choice Experiments we investigate the relationship between HLC and willingness to change lifestyle, in terms of eating habits, physical activity and associated cardiovascular disease risk, in a 384 person sample representative of the 40–65 aged population of Northern Ireland administered between February and July 2011. Using latent class analysis we identify three discrete classes of people based on their HLC: the first class is sceptical about their capacity to control their health and certain unhealthy habits. Despite being unsatisfied with their situation, they are reluctant to accept behaviour changes. The second is a group of individuals unhappy with their current situation but willing to change through exercise and diet. Finally, a group of healthy optimists is identified, who are satisfied with their current situation but happy to take more physical activity and improve their diet. Our findings show that any policy designed to modify people's health related behaviour should consider the needs of this sceptical class which represents a considerable proportion of the population in the region.

Modelling the impact of antibiotic use and infection control practices on the incidence of hospital-acquired methicillin-resistant Staphylococcus aureus: a time-series analysis

Objectives: Methicillin-resistant Staphylococcus aureus (MRSA) is a major nosocomial pathogen worldwide. A wide range of factors have been suggested to influence the spread of MRSA. The objective of this study was to evaluate the effect of antimicrobial drug use and infection control practices on nosocomial MRSA incidence in a 426-bed general teaching hospital in Northern Ireland.

Methods: The present research involved the retrospective collection of monthly data on the usage of antibiotics and on infection control practices within the hospital over a 5 year period (January 2000–December 2004). A multivariate ARIMA (time-series analysis) model was built to relate MRSA incidence with antibiotic use and infection control practices.

Results: Analysis of the 5 year data set showed that temporal variations in MRSA incidence followed temporal variations in the use of fluoroquinolones, third-generation cephalosporins, macrolides and amoxicillin/clavulanic acid (coefficients = 0.005, 0.03, 0.002 and 0.003, respectively, with various time lags). Temporal relationships were also observed between MRSA incidence and infection control practices, i.e. the number of patients actively screened for MRSA (coefficient = -0.007), the use of alcohol-impregnated wipes (coefficient = -0.0003) and the bulk orders of alcohol-based handrub (coefficients = -0.04 and -0.08), with increased infection control activity being associated with decreased MRSA incidence, and between MRSA incidence and the number of new patients admitted with MRSA (coefficient = 0.22). The model explained 78.4% of the variance in the monthly incidence of MRSA.

Conclusions: The results of this study confirm the value of infection control policies as well as suggest the usefulness of restricting the use of certain antimicrobial classes to control MRSA.

Phosphoramidates of 2'-beta-D-arabinouridine (AraU) as phosphate prodrugs; design, synthesis, in vitro activity and metabolism

2'-Beta-D-arabinouridine (AraU), the uridine analogue of the anticancer agent AraC, was synthesized and evaluated for antiviral activity and cytotoxicity. In addition, a series of AraU monophosphate prodrugs in the form of triester phosphoramidates (ProTides) were also synthesized and tested against a range of viruses, leukaemia and solid tumour cell lines. Unfortunately, neither the parent compound (AraU) nor any of its ProTides showed antiviral activity, nor potent inhibitory activity against any of the cancer cell lines. Therefore, the metabolism of AraU phosphoramidates to release AraU monophosphate was investigated. The results showed carboxypeptidase Y, hog liver esterase and crude CEM tumor cell extracts to hydrolyse the ester motif of phosphoramidates with subsequent loss of the aryl group, while molecular modelling studies suggested that the AraU l-alanine aminoacyl phosphate derivative might not be a good substrate for the phosphoramidase enzyme Hint-1. These findings are in agreement with the observed disappearance of intact prodrug and concomitant appearance of the corresponding phosphoramidate intermediate derivative in CEM cell extracts without measurable formation of araU monophosphate. These findings may explain the poor antiviral/cytostatic potential of the prodrugs.

Modelling the response of fresh groundwater to climate and vegetation changes in coral islands

In coral islands, groundwater is a crucial freshwater resource for terrestrial life, including human water supply. Response of the freshwater lens to expected climate changes and subsequent vegetation alterations is quantified for Grande Glorieuse, a low-lying coral island in the Western Indian Ocean. Distributed models of recharge, evapotranspiration and saltwater phytotoxicity are integrated into a variable-density groundwater model to simulate the evolution of groundwater salinity. Model results are assessed against field observations including groundwater and geophysical measurements. Simulations show the major control currently exerted by the vegetation with regards to the lens morphology and the high sensitivity of the lens to climate alterations, impacting both quantity and salinity. Long-term changes in mean sea level and climatic conditions (rainfall and evapotranspiration) are predicted to be responsible for an average increase in salinity approaching 140 % (+8 kg m-3) when combined. In low-lying areas with high vegetation density, these changes top +300 % (+10 kg m-3). However, due to salinity increase and its phytotoxicity, it is shown that a corollary drop in vegetation activity can buffer the alteration of fresh groundwater. This illustrates the importance of accounting for vegetation dynamics to study groundwater in coral islands.

A review of rhizosphere carbon flow modelling

Rhizosphere processes play a key role in nutrient cycling in terrestrial ecosystems. Plant rhizodeposits supply low-molecular weight carbon substrates to the soil microbial community, resulting in elevated levels of activity surrounding the root. Mechanistic compartmental models that aim to model carbon flux through the rhizosphere have been reviewed and areas of future research necessary to better calibrate model parameters have been identified. Incorporating the effect of variation in bacterial biomass physiology on carbon flux presents a considerable challenge to experimentalists and modellers alike due to the difficulties associated with differentiating dead from dormant cells. A number of molecular techniques that may help to distinguish between metabolic states of bacterial cells are presented. The calibration of growth, death and maintenance parameters in rhizosphere models is also discussed. A simple model of rhizosphere carbon flow has been constructed and a sensitivity analysis was carried out on the model to highlight which parameters were most influential when simulating carbon flux. It was observed that the parameters that most heavily influenced long-term carbon compartmentalisation in the rhizosphere were exudation rate and biomass yield. It was concluded that future efforts to simulate carbon flow in the rhizosphere should aim to increase ecological realism in model structure.

Modelling Future Coronary Heart Disease Mortality to 2030 in the British Isles

OBJECTIVE: Despite rapid declines over the last two decades, coronary heart disease (CHD) mortality rates in the British Isles are still amongst the highest in Europe. This study uses a modelling approach to compare the potential impact of future risk factor scenarios relating to smoking and physical activity levels, dietary salt and saturated fat intakes on future CHD mortality in three countries: Northern Ireland (NI), Republic of Ireland (RoI) and Scotland.

METHODS: CHD mortality models previously developed and validated in each country were extended to predict potential reductions in CHD mortality from 2010 (baseline year) to 2030. Risk factor trends data from recent surveys at baseline were used to model alternative future risk factor scenarios: Absolute decreases in (i) smoking prevalence and (ii) physical inactivity rates of up to 15% by 2030; relative decreases in (iii) dietary salt intake of up to 30% by 2030 and (iv) dietary saturated fat of up to 6% by 2030. Probabilistic sensitivity analyses were then conducted.

RESULTS: Projected populations in 2030 were 1.3, 3.4 and 3.9 million in NI, RoI and Scotland respectively (adults aged 25-84). In 2030: assuming recent declining mortality trends continue: 15% absolute reductions in smoking could decrease CHD deaths by 5.8-7.2%. 15% absolute reductions in physical inactivity levels could decrease CHD deaths by 3.1-3.6%. Relative reductions in salt intake of 30% could decrease CHD deaths by 5.2-5.6% and a 6% reduction in saturated fat intake might decrease CHD deaths by some 7.8-9.0%. These projections remained stable under a wide range of sensitivity analyses.

CONCLUSIONS: Feasible reductions in four cardiovascular risk factors (already achieved elsewhere) could substantially reduce future coronary deaths. More aggressive polices are therefore needed in the British Isles to control tobacco, promote healthy food and increase physical activity.

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.

Application of GPCR Structures for Modelling of Free Fatty Acid Receptors

Five G protein-coupled receptors (GPCRs) have been identified to be activated by free fatty acids (FFA). Among them, FFA1 (GPR40) and FFA4 (GPR120) bind long-chain fatty acids, FFA2 (GPR43) and FFA3 (GPR41) bind short-chain fatty acids and GPR84 binds medium-chain fatty acids. Free fatty acid receptors have now emerged as potential targets for the treatment of diabetes, obesity and immune diseases. The recent progress in crystallography of GPCRs has now enabled the elucidation of the structure of FFA1 and provided reliable templates for homology modelling of other FFA receptors. Analysis of the crystal structure and improved homology models, along with mutagenesis data and structure activity, highlighted an unusual arginine charge pairing interaction in FFA1-3 for receptor modulation, distinct structural features for ligand binding to FFA1 and FFA4 and an arginine of the second extracellular loop as a possible anchoring point for FFA at GPR84. Structural data will be helpful for searching novel small molecule modulators at the FFA receptors.