Preventing type 2 diabetes mellitus in Qatar by reducing obesity, smoking, and physical inactivity: mathematical modeling analyses.

BACKGROUND: The aim of this study was to estimate the impact of reducing the prevalence of obesity, smoking, and physical inactivity, and introducing physical activity as an explicit intervention, on the burden of type 2 diabetes mellitus (T2DM), using Qatar as an example. METHODS: A population-level mathematical model was adapted and expanded. The model was stratified by sex, age group, risk factor status, T2DM status, and intervention status, and parameterized by nationally representative data. Modeled interventions were introduced in 2016, reached targeted level by 2031, and then maintained up to 2050. Diverse intervention scenarios were assessed and compared with a counter-factual no intervention baseline scenario. RESULTS: T2DM prevalence increased from 16.7% in 2016 to 24.0% in 2050 in the baseline scenario. By 2050, through halting the rise or reducing obesity prevalence by 10-50%, T2DM prevalence was reduced by 7.8-33.7%, incidence by 8.4-38.9%, and related deaths by 2.1-13.2%. For smoking, through halting the rise or reducing smoking prevalence by 10-50%, T2DM prevalence was reduced by 0.5-2.8%, incidence by 0.5-3.2%, and related deaths by 0.1-0.7%. For physical inactivity, through halting the rise or reducing physical inactivity prevalence by 10-50%, T2DM prevalence was reduced by 0.5-6.9%, incidence by 0.5-7.9%, and related deaths by 0.2-2.8%. Introduction of physical activity with varying intensity at 25% coverage reduced T2DM prevalence by 3.3-9.2%, incidence by 4.2-11.5%, and related deaths by 1.9-5.2%. CONCLUSIONS: Major reductions in T2DM incidence could be accomplished by reducing obesity, while modest reductions could be accomplished by reducing smoking and physical inactivity, or by introducing physical activity as an intervention

Genomic markers to tailor treatments: waiting or initiating?

The decade since the publication of the Human Genome Project draft has ended with the discovery of hundreds of genomic markers related to diseases and phenotypes. However, the project has not yet delivered on its promise to tailor treatments for individuals. The number of genomic markers in clinical practice is very small. The number of markers to guide treatment decisions is even smaller. In order to speed up discovery and validation of genomic treatment selection markers, we call for considering the brilliant potential of randomized clinical trials. If biomedical research community can collaborate in organizing large-scale consortium of clinical trials associated with well-designed biobanks, these studies would soon act as huge laboratories for investigating genomic medicine; a big step forward towards personalizing medicine

Electronic Cigarette Advertising Impacts Adversely on Smoking Behaviour Within a London Student Cohort: A Cross-Sectional Structured Survey.

INTRODUCTION: In contrast to tobacco smoking, electronic cigarette ("vaping") advertisement had been approved in the United Kingdom (UK) in January 2013. Currently, there are an estimated 3.2 million UK e-cigarette users. The impact of e-cigarette advertisement on tobacco use has not been studied in detail. We hypothesised that e-cigarette advertisement impacts on conventional smoking behaviour. METHODS: A cross-sectional structured survey assessed the impact of e-cigarette advertising on the perceived social acceptability of cigarette and e-cigarette smoking and on using either cigarettes or e-cigarettes (on a scale of 1 to 5/'not at all' to 'a lot'). The survey was administered between January to March 2015 to London university students, before and after viewing 5 UK adverts including a TV commercial. RESULTS: Data were collected from 106 participants (22 ± 2 years, 66% male), comprising cigarette smokers (32%), non-smokers (54%) and ex-smokers (14%). This included vapers (16%), non-vapers (77%) and ex-vapers (7%). After viewing the adverts, smokers (2.6 ± 1.0 vs. 3.8 ± 1.1, p = 0.001) and non-smokers (3.2 ± 0.7 vs. 3.7 ± 0.8, p = 0.007) felt smoking was more socially acceptable, compared to before viewing them. Participants were more likely to try both e-cigarettes (1.90 ± 1.03 to 3.09 ± 1.11, p < 0.001) and conventional cigarettes (1.73 ± 0.83 to 2.27 ± 1.13, p < 0.001) after viewing the adverts compared to before. Vapers were less likely to smoke both an e-cigarette, and a conventional cigarette after viewing the adverts. CONCLUSION: E-cigarette advertising encourages both e-cigarette and conventional cigarette use in young smokers and non-smokers. The adverts increase the social acceptability of smoking without regarding the importance of public health campaigns that champion smoking cessation

Universal health coverage from multiple perspectives: a synthesis of conceptual literature and global debates

Background: There is an emerging global consensus on the importance of universal health coverage (UHC), but no unanimity on the conceptual definition and scope of UHC, whether UHC is achievable or not, how to move towards it, common indicators for measuring its progress, and its long-term sustainability. This has resulted in various interpretations of the concept, emanating from different disciplinary perspectives. This paper discusses the various dimensions of UHC emerging from these interpretations and argues for the need to pay attention to the complex interactions across the various components of a health system in the pursuit of UHC as a legal human rights issue. Discussion: The literature presents UHC as a multi-dimensional concept, operationalized in terms of universal population coverage, universal financial protection, and universal access to quality health care, anchored on the basis of health care as an international legal obligation grounded in international human rights laws. As a legal concept, UHC implies the existence of a legal framework that mandates national governments to provide health care to all residents while compelling the international community to support poor nations in implementing this right. As a humanitarian social concept, UHC aims at achieving universal population coverage by enrolling all residents into health-related social security systems and securing equitable entitlements to the benefits from the health system for all. As a health economics concept, UHC guarantees financial protection by providing a shield against the catastrophic and impoverishing consequences of out-of-pocket expenditure, through the implementation of pooled prepaid financing systems. As a public health concept, UHC has attracted several controversies regarding which services should be covered: comprehensive services vs. minimum basic package, and priority disease-specific interventions vs. primary health care. Summary: As a multi-dimensional concept, grounded in international human rights laws, the move towards UHC in LMICs requires all states to effectively recognize the right to health in their national constitutions. It also requires a human rights-focused integrated approach to health service delivery that recognizes the health system as a complex phenomenon with interlinked functional units whose effective interaction are essential to reach the equilibrium called UHC

The effects of spatial population dataset choice on estimates of population at risk of disease

Background: The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example.Methods: The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets.Results: The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets.Conclusions: Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. © 2011 Tatem et al; licensee BioMed Central Ltd.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Reassessment of the 2010-2011 Haiti cholera outbreak and rainfall-driven multiseason projections

Mathematical models can provide key insights into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. We study the ex post reliability of predictions of the 2010-2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. We consider the impact of different approaches to the modeling of spatial spread of Vibrio cholerae and mechanisms of cholera transmission, accounting for the dynamics of susceptible and infected individuals within different local human communities. To explain resurgences of the epidemic, we go on to include waning immunity and a mechanism explicitly accounting for rainfall as a driver of enhanced disease transmission. The formal comparative analysis is carried out via the Akaike information criterion (AIC) to measure the added information provided by each process modeled, discounting for the added parameters. A generalized model for Haitian epidemic cholera and the related uncertainty is thus proposed and applied to the year-long dataset of reported cases now available. The model allows us to draw predictions on longer-term epidemic cholera in Haiti from multiseason Monte Carlo runs, carried out up to January 2014 by using suitable rainfall fields forecasts. Lessons learned and open issues are discussed and placed in perspective. We conclude that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control

Subjectivity in a context of environmental change: opening new dialogues in mental health research

In a period of unstable experimentation with challenges of globalization of associated risks, and disenchantment with ‘enduring injustice’, we bring forward a consideration of subjectivity to the study of environmental change and mental health. We begin by identifying how mainstream climate change and mental health studies are unable to explain the emergent and co-evolutionary pathways of agency. As a means of freeing these studies of their objective dimensions of linear-causation, we argue in favour of a re-positioning of subjectivity within an appreciation of recognition conflicts and beyond the over-deterministic interpretations of power centres—state, market or religion. We draw on one example of scientific research that was conducted in a region undergoing strong environmental, social and cultural changes, in the state of São Paulo/Brazil, with the aim to open mental health research to new dialogues, to which we contribute with the notion of the ‘pluriversal subject’

Food Price Shocks and the Political Economy of Global Agricultural and Development Policy

The recent spikes of global food prices induced a rapid increase in mass media coverage, public policy attention, and donor funding for food security and for agriculture and rural poverty. This has occurred while the shift from low to high food prices has induced a shift in (demographic or social) location of the hunger and poverty effects, but the total number of undernourished and poor people has declined over the same period. We suggest that the observed pattern can be explained by the presence of a global urban bias on agriculture and food policy in developing countries, and we discuss whether this global urban bias may actually benefit poor farmers. We argue that the food price spikes have succeeded where others have failed in the past: to move the problems of poor and hungry farmers to the top of the policy agenda and to induce development and donor strategies to help them