Evaluation of the impact of orally administered carbohydrates on postprandial blood glucose levels in different pre-clinical models

ABSTRACT We developed a pre-clinical model in which to evaluate the impact of orally administered carbohydrates on postprandial blood glucose levels. For this purpose, we compared the effects of different carbohydrates with well-established glycemic indexes. We orally administered (gavage) increasing amounts (0.2, 0.4, 0.6, 0.8, and 1.0 g/kg) of sucrose and lactose to rats which had been fasted for 6 h or 15 h, respectively. In part of the experiments we administered frutose (gavagem). Three different models were compared for measuring postprandial blood glucose levels: a) evaluation of interstitial glucose concentrations by using a real time continuous glucose monitoring system; b) evaluation of glucose levels in blood obtained from the rat tail; c) evaluation of serum glucose levels in blood collected after decapitation. Our results showed that blood obtained from the tails of 15-h fasted rats was the best model in which to evaluate the effect of carbohydrates on postprandial blood glucose levels.

An Agent-Based Model for Addressing the Impact of a Disaster on Access to Primary Care Services.

OBJECTIVE: Hurricane Sandy in the Rockaways, Queens, forced residents to evacuate and primary care providers to close or curtail operations. A large deficit in primary care access was apparent in the immediate aftermath of the storm. Our objective was to build a computational model to aid responders in planning to situate primary care services in a disaster-affected area. METHODS: Using an agent-based modeling platform, HAZEL, we simulated the Rockaways population, its evacuation behavior, and primary care providers' availability in the aftermath of Hurricane Sandy. Data sources for this model included post-storm and community health surveys from New York City, a survey of the Rockaways primary care providers, and research literature. The model then tested geospatially specific interventions to address storm-related access deficits. RESULTS: The model revealed that areas of high primary care access deficit were concentrated in the eastern part of the Rockaways. Placing mobile health clinics in the most populous census tracts reduced the access deficit significantly, whereas increasing providers' capacity by 50% reduced the deficit to a lesser degree. CONCLUSIONS: An agent-based model may be a useful tool to have in place so that policy makers can conduct scenario-based analyses to plan interventions optimally in the event of a disaster. (Disaster Med Public Health Preparedness. 2016;10:386-393).

[Acceptance of illness scale and its clinical impact]. / Skala Akceptacji Choroby i jej znaczenie w praktyce klinicznej.

The level of chronic illness acceptance is an indicator of functioning and predictor of quality of life. The greater the acceptance of disease is, the less mental discomfort and less severe negative emotions there are. This paper presents Acceptance of Illness Scale and the main results and conclusions of the recent publications dealing with this problem in patients with chronic diseases. It has been proved that the level of acceptance of illness is significantly associated with a variety of clinical and sociodemographic factors. This justifies the rightness of its assessment, which appears to be an important element in the holistic medical and nonmedical care.

Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment.

We propose a new approach to assess the impact of traffic-related air pollution on public health by mapping personal trajectories using mobile phone tracking technology in an urban environment. Although this approach is not based on any empirical studies, we believe that this method has great potential and deserves serious attention. Mobile phone tracking technology makes it feasible to generate millions of personal trajectories and thereby cover a large fraction of an urban population. Through analysis, personal trajectories are not only associated to persons, but it can also be associated with vehicles, vehicle type, vehicle speed, vehicle emission rates, and sources of vehicle emissions. Pollution levels can be estimated by dispersion models from calculated traffic emissions. Traffic pollution exposure to individuals can be estimated based on the exposure along the individual human trajectories in the estimated pollution concentration fields by utilizing modelling tools. By data integration, one may identify trajectory patterns of particularly exposed human groups. The approach of personal trajectories may open a new paradigm in understanding urban dynamics and new perspectives in population-wide empirical public health research. This new approach can be further applied to individual commuter route planning, land use planning, urban traffic network planning, and used by authorities to formulate air pollution mitigation policies and regulations.

Quantitative health impact assessment: taking stock and moving forward.

Over the past years, application of health impact assessment has increased substantially, and there has been a strong growth of tools that allow quantification of health impacts for a range of health relevant policies. We review these developments, and conclude that further tool development is no longer a main priority, although several aspects need to be further developed, such as methods to assess impacts on health inequalities and to assess uncertainties. The main new challenges are, first, to conduct a comparative evaluation of different tools, and, second, to ensure the maintenance and continued availability of the toolkits including their data contents.