Creating an enabling legal framework fro REDD+ investments in Kenya

Reducing Emissions from Deforestation and Forest Degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+) has emerged out of the United Nations Framework Convention on Climate Change (UNFCCC)/Kyoto Protocol negotiations. It is intended to be a mechanism to channel funding (from both public and private sources) for reducing emissions from the forest sector. It is an international climate change policy that relies on national implementation. In order to attract and manage REDD+ investments (both public and private), countries need to decide on their approach to REDD+ implementation through a series of policy choices, and then implement those policy choices through strong legal frameworks. An important question for REDD+ host countries to consider, therefore, is how to develop robust legal structures to facilitate REDD+ implementation. These legal frameworks could be based on existing laws, and/or require new law making.

A legal perspective of carbon rights and benefit sharing under REDD+: A conceptual framework and examples from Cambodia and Kenya

This article discusses two key issues in REDD+ design and implementation at the national level – carbon rights, and benefit sharing. Both carbon rights and benefit sharing can be understood as new legal concepts (although they build on existing law), and as legal concepts they offer a framework for addressing related areas of REDD+ policy. Many countries are currently considering how to manage carbon rights and benefit sharing issues, including Cambodia and Kenya. Both of these countries host existing forest carbon projects and are also in the process of designing national REDD+ programmes. This article uses a conceptual framework for carbon rights and benefit sharing derived from legal analysis to consider the cases of both Cambodia and Kenya, and also includes a general discussion of the challenges countries might encounter when considering how to manage carbon rights and benefit sharing in the context of REDD+ implementation.

Physical activity and health related quality of life

Background Research on the relationship between Health Related Quality of Life (HRQoL) and physical activity (PA), to date, have rarely investigated how this relationship differ across objective and subjective measures of PA. The aim of this paper is to explore the relationship between HRQoL and PA, and examine how this relationship differs across objective and subjective measures of PA, within the context of a large representative national survey from England. Methods Using a sample of 5,537 adults (40–60 years) from a representative national survey in England (Health Survey for England 2008), Tobit regressions with upper censoring was employed to model the association between HRQoL and objective, and subjective measures of PA controlling for potential confounders. We tested the robustness of this relationship across specific types of PA. HRQoL was assessed using the summary measure of health state utility value derived from the EuroQol-5 Dimensions (EQ-5D) whilst PA was assessed via subjective measure (questionnaire) and objective measure (accelerometer- actigraph model GT1M). The actigraph was worn (at the waist) for 7 days (during waking hours) by a randomly selected sub-sample of the HSE 2008 respondents (4,507 adults – 16 plus years), with a valid day constituting 10 hours. Analysis was conducted in 2010. Results Findings suggest that higher levels of PA are associated with better HRQoL (regression coefficient: 0.026 to 0.072). This relationship is consistent across different measures and types of PA although differences in the magnitude of HRQoL benefit associated with objective and subjective (regression coefficient: 0.047) measures of PA are noticeable, with the former measure being associated with a relatively better HRQoL (regression coefficient: 0.072). Conclusion Higher levels of PA are associated with better HRQoL. Using an objective measure of PA compared with subjective shows a relatively better HRQoL.

The cost-effectiveness of exercise referral schemes

Background Exercise referral schemes (ERS) aim to identify inactive adults in the primary care setting. The primary care professional refers the patient to a third party service, with this service taking responsibility for prescribing and monitoring an exercise programme tailored to the needs of the patient. This paper examines the cost-effectiveness of ERS in promoting physical activity compared with usual care in primary care setting. Methods A decision analytic model was developed to estimate the cost-effectiveness of ERS from a UK NHS perspective. The costs and outcomes of ERS were modelled over the patient's lifetime. Data were derived from a systematic review of the literature on the clinical and cost-effectiveness of ERS, and on parameter inputs in the modelling framework. Outcomes were expressed as incremental cost per quality-adjusted life-year (QALY). Deterministic and probabilistic sensitivity analyses investigated the impact of varying ERS cost and effectiveness assumptions. Sub-group analyses explored the cost-effectiveness of ERS in sedentary people with an underlying condition. Results Compared with usual care, the mean incremental lifetime cost per patient for ERS was £169 and the mean incremental QALY was 0.008, generating a base-case incremental cost-effectiveness ratio (ICER) for ERS at £20,876 per QALY in sedentary individuals without a diagnosed medical condition. There was a 51% probability that ERS was cost-effective at £20,000 per QALY and 88% probability that ERS was cost-effective at £30,000 per QALY. In sub-group analyses, cost per QALY for ERS in sedentary obese individuals was £14,618, and in sedentary hypertensives and sedentary individuals with depression the estimated cost per QALY was £12,834 and £8,414 respectively. Incremental lifetime costs and benefits associated with ERS were small, reflecting the preventative public health context of the intervention, with this resulting in estimates of cost-effectiveness that are sensitive to variations in the relative risk of becoming physically active and cost of ERS. Conclusions ERS is associated with modest increase in lifetime costs and benefits. The cost-effectiveness of ERS is highly sensitive to small changes in the effectiveness and cost of ERS and is subject to some significant uncertainty mainly due to limitations in the clinical effectiveness evidence base.