Demand response to improved walking infrastructure: A study into the economics of walking and health behaviour change

Walking is the most common form of moderate‐intensity physical activity among adults, is widely accessible and especially appealing to obese people. Most often policy makers are interested in valuing the effect on walking of changes in some characteristics of a neighbourhood, the demand response for walking, of infrastructure changes. A positive demand response to improvements in the walking environment could help meet the public health target of 150 minutes of at least moderate‐intensity physical activity per week. We model walking in an individual’s local neighbourhood as a ‘weak complement’ to the characteristics of the neighbourhood itself. Walking is affected by neighbourhood
characteristics, substitutes, and individual’s characteristics, including their opportunity cost of time.  Using compensating variation, we assess the economic benefits of walking and how walking behaviour is affected by improvements to the neighbourhood.  Using a sample of 1,209 respondents surveyed over a 12 month period (Feb 2010‐Jan 2011) in East Belfast, United Kingdom, we find that a policy that increased walkability and people’s perception of access to shops and facilities  would lead to an increase in walking of about 36 minutes/person/week, valued at £13.65/person/week. When focusing on inactive residents, a policy that improved the walkability of the area would lead to guidelines for physical activity being reached by only 12.8% of the population who are currently inactive. Additional interventions would therefore be needed to encourage inactive residents to
achieve the recommended levels of physical activity, as it appears that interventions that improve the walkability of an area are particularly effective in increasing walking among already active citizens, and, among the inactive ones, the best response is found among healthier, younger and wealthier citizens.

Tackling the problem of blood culture contamination in the intensive care unit using an educational intervention

Blood culture contamination (BCC) has been associated with unnecessary antibiotic use, additional laboratory tests and increased length of hospital stay thus incurring significant extra hospital costs. We set out to assess the impact of a staff educational intervention programme on decreasing intensive care unit (ICU) BCC rates to <3% (American Society for Microbiology standard). BCC rates during the pre-intervention period (January 2006-May 2011) were compared with the intervention period (June 2011-December 2012) using run chart and regression analysis. Monthly ICU BCC rates during the intervention period were reduced to a mean of 3·7%, compared to 9·5% during the baseline period (P < 0·001) with an estimated potential annual cost savings of about £250 100. The approach used was simple in design, flexible in delivery and efficient in outcomes, and may encourage its translation into clinical practice in different healthcare settings.

Education, gender, and state-level disparities in the health of older Indians: Evidence from biomarker data

Using new biomarker data from the 2010 pilot round of the Longitudinal Aging Study in India (LASI), we investigate education, gender, and state-level disparities in health. We find that hemoglobin level, a marker for anemia, is lower for respondents with no schooling (0.7 g/dL less in the adjusted model) compared to those with some formal education and is also lower for females than for males (2.0 g/dL less in the adjusted model). In addition, we find that about one third of respondents in our sample aged 45 or older have high C-reaction protein (CRP) levels (>3 mg/L), an indicator of inflammation and a risk factor for cardiovascular disease. We find no evidence of educational or gender differences in CRP, but there are significant state-level disparities, with Kerala residents exhibiting the lowest CRP levels (a mean of 1.96 mg/L compared to 3.28 mg/L in Rajasthan, the state with the highest CRP). We use the Blinder–Oaxaca decomposition approach to explain group-level differences, and find that state-level disparities in CRP are mainly due to heterogeneity in the association of the observed characteristics of respondents with CRP, rather than differences in the distribution of endowments across the sampled state populations.

Can less be more? Comparison of an 8-item placement quality measure with the 50-item Dundee Ready Educational Environment Measure (DREEM)

Clinical clerks learn more than they are taught and not all they learn can be measured. As a result, curriculum leaders evaluate clinical educational environments. The quantitative Dundee Ready Environment Measure (DREEM) is a de facto standard for that purpose. Its 50 items and 5 subscales were developed by consensus. Reasoning that an instrument would perform best if it were underpinned by a clearly conceptualized link between environment and learning as well as psychometric evidence, we developed the mixed methods Manchester Clinical Placement Index (MCPI), eliminated redundant items, and published validity evidence for its 8 item and 2 subscale structure. Here, we set out to compare MCPI with DREEM. 104 students on full-time clinical placements completed both measures three times during a single academic year. There was good agreement and at least as good discrimination between placements with the smaller MCPI. Total MCPI scores and the mean score of its 5-item learning environment subscale allowed ten raters to distinguish between the quality of educational environments. Twenty raters were needed for the 3-item MCPI training subscale and the DREEM scale and its subscales. MCPI compares favourably with DREEM in that one-sixth the number of items perform at least as well psychometrically, it provides formative free text data, and it is founded on the widely shared assumption that communities of practice make good learning environments.

Economics of Non-Communicable Diseases in Indonesia

The Economics of Non-Communicable Diseases in Indonesia provides new data on the economic burden of NCDs in the country, and puts it in perspective by drawing a comparison with India and China. With this new addition to the series on the economics of NCDs, the World Economic Forum aims to advance the understanding of the expected economic output loss at the country level, particularly in countries in economic and epidemiological transition. The evidence presented provides a starting point in reorienting the dialogue on investing in healthy living and NCD prevention in Indonesia towards the view that a healthy population is an important factor for sustainable growth.

Paving the way for the use of the SDQ in economic evaluations of school-based population health interventions: an empirical analysis of the external validity of SDQ mapping algorithms to the CHU9D in an educational setting

Purpose
The Strengths and Difficulties Questionnaire (SDQ) is a behavioural screening tool for children. The SDQ is increasingly used as the primary outcome measure in population health interventions involving children, but it is not preference based; therefore, its role in allocative economic evaluation is limited. The Child Health Utility 9D (CHU9D) is a generic preference-based health-related quality of-life measure. This study investigates the applicability of the SDQ outcome measure for use in economic evaluations and examines its relationship with the CHU9D by testing previously published mapping algorithms. The aim of the paper is to explore the feasibility of using the SDQ within economic evaluations of school-based population health interventions.
Methods
Data were available from children participating in a cluster randomised controlled trial of the school-based roots of empathy programme in Northern Ireland. Utility was calculated using the original and alternative CHU9D tariffs along with two SDQ mapping algorithms. t tests were performed for pairwise differences in utility values from the preference-based tariffs and mapping algorithms.
Results
Mean (standard deviation) SDQ total difficulties and prosocial scores were 12 (3.2) and 8.3 (2.1). Utility values obtained from the original tariff, alternative tariff, and mapping algorithms using five and three SDQ subscales were 0.84 (0.11), 0.80 (0.13), 0.84 (0.05), and 0.83 (0.04), respectively. Each method for calculating utility produced statistically significantly different values except the original tariff and five SDQ subscale algorithm.
Conclusion
Initial evidence suggests the SDQ and CHU9D are related in some of their measurement properties. The mapping algorithm using five SDQ subscales was found to be optimal in predicting mean child health utility. Future research valuing changes in the SDQ scores would contribute to this research.