What do we need for robust and quantitative health impact assessment?

Health impact assessment (HIA) aims to make the health consequences of decisions explicit. Decision-makers need to know that the conclusions of HIA are robust. Quantified estimates of potential health impacts may be more influential but there are a number of concerns. First, not everything that can be quantified is important. Second, not everything that is being quantified at present should be, if this cannot be done robustly. Finally, not everything that is important can be quantified; rigorous qualitative HIA will still be needed for a thorough assessment. This paper presents the first published attempt to provide practical guidance on what is required to perform robust, quantitative HIA. Initial steps include profiling the affected populations, obtaining evidence from for postulated impacts, and determining how differences in subgoups' exposures and suscepibilities affect impacts. Using epidemiological evidence for HIA is different from carrying out a new study. Key steps in quantifying impacts are mapping the causal pathway, selecting appropriate outcome measures and selecting or developing a statistical model. Evidence from different sources is needed. For many health impacts, evidence of an effect may be scarce and estimates of the size and nature of the relationship may be inadequate. Assumptions and uncertainties must therefore be explicit. Modelled data can sometimes be tested against empirical data but sensitivity analyses are crucial. When scientific problems occur, discontinuing the study is not an option, as HIA is usually intended to inform real decisions. Both qualitative and quantitative elements of HIA must be performed robustly to be of value

NewsPad: Designing for Collaborative Storytelling in Neighborhoods

This paper introduces design explorations in neighborhood collaborative storytelling. We focus on blogs and citizen journalism, which have been celebrated as a means to meet the reporting needs of small local communities. These bloggers have limited capacity and social media feeds seldom have the context or readability of news stories. We present NewsPad, a content editor that helps communities create structured stories, collaborate in real time, recruit contributors, and syndicate the editing process. We evaluate NewsPad in four pilot deployments and find that the design elicits collaborative story creation.Comment: NewsPad: designing for collaborative storytelling in neighborhoods. In Proceedings of the extended abstracts of the 32nd annual ACM conference on Human factors in computing systems (CHI EA 2014

Respiratory hospital admission risk near large composting facilities

AbstractBackgroundLarge-scale composting can release bioaerosols in elevated quantities, but there are few studies of health effects on nearby communities.MethodsA cross-sectional ecological small area design was used to examine risk of respiratory hospital admissions within 2500m of all 148 English large-scale composting facilities in 2008–10. Statistical analyses used a random intercept Poisson regression model at Census Output Area (COA) level (mean population 310). Models were adjusted for age, sex, deprivation and tobacco sales.ResultsAnalysing 34,963 respiratory hospital admissions in 4656 COAs within 250–2500m of a site, there were no significant trends using pre-defined distance bands of >250–750m, >750–1500m and >1500–2500m. Using a continuous measure of distance, there was a small non-statistically significant (p=0.054) association with total respiratory admissions corresponding to a 1.5% (95% CI: 0.0–2.9%) decrease in risk if moving from 251m to 501m. There were no significant associations for subgroups of respiratory infections, asthma or chronic obstructive pulmonary disease.ConclusionThis national study does not provide evidence for increased risks of respiratory hospital admissions in those living beyond 250m of an outdoor composting area perimeter. Further work using better measures of exposure and exploring associations with symptoms and disease prevalence, especially in vulnerable groups, is recommended to support regulatory approaches

Organic nitrogen in aerosols and precipitation at Barbados and Miami: Implications regarding sources, transport and deposition to the western subtropical North Atlantic

The deposition of anthropogenic nitrogen (N) species is believed to have a significant impact on the oligotrophic North Atlantic, but the magnitude of ecological effects remains uncertain because the deposition of water soluble organic N (WSON) is poorly quantified. Here we present measurements of water soluble inorganic N (WSIN) and WSON in aerosol and rain at two subtropical North Atlantic time series sites: Barbados and Miami. WSON total deposition rates ranged from 17.9 mmol m−2 yr−1 to 49.6 mmol m−2 yr−1, contributing on average only 6–14% of total N deposition, less than half the poorly constrained global average which is typically cited as 30%. On an event basis, biomass burning and dust events yielded the largest concentrations of WSON. However, biomass burning was relatively infrequent and highly variable in composition, and much of the organic N associated with dust appeared to be externally adsorbed from pollution sources. Conversely, in Miami pollution made relatively small contributions of WSON on an event basis, but impacts were relatively frequent, making pollution one of the largest sources of WSON during the year. The largest contributor to WSON was volatile basic organic N (VBON) species, which were present at concentrations 1–2 times higher than particulate WSON. Despite VBON inputs, samples associated with pollution-source trajectories yielded much more inorganic N than WSON. Consequently, we would expect that in the future as anthropogenic N emissions increase, inorganic nitrogen will remain the dominant form of N that is deposited to the western North Atlantic

Atypical chemokine receptor ACKR2 controls branching morphogenesis in the developing mammary gland

Macrophages are important regulators of branching morphogenesis during development and postnatally in the mammary gland. Regulation of macrophage dynamics during these processes can therefore have a profound impact on development. We demonstrate here that the developing mammary gland expresses high levels of inflammatory CC-chemokines, which are essential in vivo regulators of macrophage migration. We further demonstrate that the atypical chemokine receptor ACKR2, which scavenges inflammatory CC-chemokines, is differentially expressed during mammary gland development. We have previously shown that ACKR2 regulates macrophage dynamics during lymphatic vessel development. Here, we extend these observations to reveal a novel role for ACKR2 in regulating the postnatal development of the mammary gland. Specifically, we show that Ackr2−/− mice display precocious mammary gland development. This is associated with increased macrophage recruitment to the developing gland and increased density of the ductal epithelial network. These data demonstrate that ACKR2 is an important regulator of branching morphogenesis in diverse biological contexts and provide the first evidence of a role for chemokines and their receptors in postnatal development processes

Using ecological propensity score to adjust for missing confounders in small area studies

Small area ecological studies are commonly used in epidemiology to assess the impact of area level risk factors on health outcomes when data are only available in an aggregated form. However, the resulting estimates are often biased due to unmeasured confounders, which typically are not available from the standard administrative registries used for these studies. Extra information on confounders can be provided through external data sets such as surveys or cohorts, where the data are available at the individual level rather than at the area level; however, such data typically lack the geographical coverage of administrative registries. We develop a framework of analysis which combines ecological and individual level data from different sources to provide an adjusted estimate of area level risk factors which is less biased. Our method (i) summarizes all available individual level confounders into an area level scalar variable, which we call ecological propensity score (EPS), (ii) implements a hierarchical structured approach to impute the values of EPS whenever they are missing, and (iii) includes the estimated and imputed EPS into the ecological regression linking the risk factors to the health outcome. Through a simulation study, we show that integrating individual level data into small area analyses via EPS is a promising method to reduce the bias intrinsic in ecological studies due to unmeasured confounders; we also apply the method to a real case study to evaluate the effect of air pollution on coronary heart disease hospital admissions in Greater London