Geographic Unit Of Analysis Research Articles

Population in floodplains or close to sea level increased in US but declined in some counties—especially among Black residents

Previous studies estimating US population vulnerable to climate change have assumed that population is uniformly distributed within the geographical unit of analysis, typically a census block. That assumption overstates vulnerable population in places where people have avoided the most hazardous areas. After using independent samples of housing location and building footprints to validate a revised approach, this letter estimates the US population close to sea level and in floodplains based on the assumption that population in a hazard zone is proportional to the fraction of buildings in the hazard zone, for the period 1990–2020. The building-based assumption reduces population estimates about 30%. Over the 30-year period, the US population below 1 m increased 14%–18% from 1.85 (±0.19) million in 1990 to 2.2 (±0.25) million; population below 3 m increased 31%. Sea level rise accounts for 75% of the increase in population below 1 m, but only 14% of the increase below 3 m. Nevertheless, in 21 counties, net emigration from land below 1 m was greater than 1% of county population. Although this emigration was particularly great in the 2000s after Hurricane Katrina, it totaled 170 000 for the entire 30-year period. Similarly, the US population of inland 100-year floodplains increased 7%, but several hundred counties saw a steady emigration throughout the 30-year period which totaled about 240 000. Black residents accounted for 19% of the population below 1 m but only 12% of the nation’s population in 2020, meaning that Black residents were 63% more likely to live below 1 m than the general population nationwide. This disproportionality is more attributable to high Black populations in the most vulnerable localities (especially New Orleans) than to historic segregation. Black people also are almost five times as likely to have emigrated from land below 1 m than the general population since 1990.

Assessment of Population-Level Disadvantage Indices to Inform Equitable Health Policy.

There has been unprecedented uptake of disadvantage indices such as the Centers for Disease Control and Prevention Social Vulnerability Index (SVI) to identify place-based patterns of social risk and guide equitable health policy during the COVID-19 pandemic. However, limited evidence around data elements, interoperability, and implementation leaves unanswered questions regarding the utility of indices to prioritize health equity. We identified disadvantage indices that were (a) used three or more times from 2018 to 2021, (b) designed using national-level data, and (c) available at the census-tract or block-group level. We used a network visualization to compare social determinants of health (SDOH) domains across indices. We then used geospatial analyses to compare disadvantage profiles across indices and geographic areas. We identified 14 indices. All incorporated data from public sources, with half using only American Community Survey data (n = 7) and the other half combining multiple sources (n = 7). Indices differed in geographic granularity, with county level (n = 5) and census-tract level (n = 5) being the most common. Most states used the SVI during the pandemic. The SVI, the Area Deprivation Index (ADI), the COVID-19 Community Vulnerability Index (CCVI), and the Child Opportunity Index (COI) met criteria for further analysis. Selected indices shared five indicators (income, poverty, English proficiency, no high school diploma, unemployment) but varied in other metrics and construction method. While mapping of social risk scores in Durham County, North Carolina; Cook County, Illinois; and Orleans Parish, Louisiana, showed differing patterns within the same locations depending on choice of disadvantage index, risk scores across indices showed moderate to high correlation (rs 0.7-1). However, spatial autocorrelation analyses revealed clustering, with discrepant distributions of social risk scores between different indices. Existing disadvantage indices use varied metrics to represent place-based social risk. Within the same geographic area, different indices can provide differences in social risk values and interpretations, potentially leading to varied public health or policy responses.

Assessment of Urban Heat Islands and Land Cover Types in Relation to Vulnerable Populations

This study aims to assess urban heat islands and land cover types in relation to vulnerable populations. The city of Richmond, Virginia was selected as the study area using the Census Block Group as the geographic unit of analysis. Regression analysis was carried out to examine the impacts of land cover types on ambient temperatures, while correlation analysis was used to assess the relationship between ambient temperature and vulnerable populations. Lastly, multivariate clustering analysis was performed to identify areas vulnerable to urban heat in the city. Findings suggest that: (1) impervious surfaces lead to higher ambient temperatures, while tree coverage has a cooling effect on urban heat; (2) vulnerable populations, except for older adults, tend to live in areas with higher ambient temperatures; and (3) vulnerable populations are spatially clustered in specific locations in the city. This study concludes with recommendations of mitigation measures to reduce the adverse effect of urban heat islands by applying high-albedo materials to urban surfaces and expanding tree coverage and green space.

Red sport, blue sport: political ideology and the popularity of sports in the United States

ABSTRACT This exploratory study examines correlations between political ideology and the popularity of 53 sports in the United States using geographical units of analysis. Regional interest in sports was measured using Google Trends search data from Nielsen’s 207 designated media market areas. Voting data from the 2020 Presidential Election (percent Trump vote) was used to characterise each area’s political ideology. A measure of the sports’ cultural dominance was developed through a large-scale, computer-aided content analysis of sports news. Areas with high levels of Trump support tended to favour dominant sports like football, basketball and baseball and showed less interest in fringe sports like ultimate Frisbee, rock climbing and badminton. These correlations generally held for large, mid-sized and small areas. There were, however, sports that contradicted this relationship. Focusing on outliers and inconsistent cases, the study concludes by suggesting next steps for establishing a robust link between political orientation and sport popularity.

Identifying a spatial scale for the analysis of residential burglary: An empirical framework based on point pattern analysis.

A key issue in the spatial and temporal analysis of residential burglary is the choice of scale: spatial patterns might differ appreciably for different time periods and vary across geographic units of analysis. Based on point pattern analysis of burglary incidents in Columbus, Ohio during a 9-year period, this study develops an empirical framework to identify a useful spatial scale and its dependence on temporal aggregation. Our analysis reveals that residential burglary in Columbus clusters at a characteristic scale of 2.2 km. An ANOVA test shows no significant impact of temporal aggregation on spatial scale of clustering. This study demonstrates the value of point pattern analysis in identifying a scale for the analysis of crime patterns. Furthermore, the characteristic scale of clustering determined using our method has great potential applications: (1) it can reflect the spatial environment of criminogenic processes and thus be used to define the spatial boundary for place-based policing; (2) it can serve as a candidate for the bandwidth (search radius) for hot spot policing; (3) its independence of temporal aggregation implies that police officials need not be concerned about the shifting sizes of risk-areas depending on the time of the year.

Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States.

OBJECTIVESThis study examined the spatiotemporal epidemiological status of diabetes-related death in relation to school district boundaries in the state of Michigan, United States.METHODSA retrospective observational study was conducted using death records spanning the years 2007–2014 in Michigan, with school districts as the geographic unit of analysis. Geocoding was performed for each death record. Cluster analysis used spatial autocorrelation with local Moran’s I, and spatiotemporal analysis used the Space Time Pattern Mining tool in ArcGIS Pro 2.1.RESULTSThe study revealed spatial clusters of high-high locations of diabetes-related mortality rate by school district in Michigan from 2007 to 2014. Spatiotemporal analysis showed grids with intensifying, consecutive, sporadic, and persistent hotspots of diabetes-related death in the Lansing, Royal Oak, Flint City, Berkley, Detroit City, East Lansing, South Lake, and Holt public school districts. These school districts should be prioritized for school-based diabetes prevention programsCONCLUSIONSThe study demonstrated the presence of various hotspots of diabetes-related deaths within the state of Michigan across the 8-year period of analysis. Understanding spatial and temporal hotspots could further improve our ability to evaluate diabetes burden across both time and space.

1 Correlation Between New York City Hot Spotting Policy and Mobility to Reduce COVID-19 Spread

In October 2020, New York State initiated a micro-cluster strategy (“hot spotting”) that divides into three categories based on COVID-19 cases and hospital capacity, each with successively more restrictions: Yellow, Orange, and Red Zones. Our objectives were to evaluate the influence of hot spotting on mobility and subsequent mortality, and then to identify underlying social determinants of health associated with the neighborhoods most affected by hot spotting. We combine several data sources in our analysis. Time-dependent data were obtained from SafeGraph for cellphone mobility at the Census Block Group, New York State Governor’s Office for hot spotting, school and indoor dining, and NYC Department of Health and Mental Hygiene (DOHMH) for COVID-19 cases and mortality. Using the DOHMH’s “Modified Zip Code Tabulation Areas” (MODZCTA), we matched these to community-level data obtained from 2018 American Community Survey 5-year estimates for population density. Our main outcomes are Average Median Percentage Time Home (AMPTH) and Device-Weighted Average Median Percentage Time Home (DWAMPTH) from SafeGraph Social Distancing Metrics summarized to MODZCTA boundaries. Home is defined as the common nighttime location of each mobile device over a 6-week period to a Geohash-7 granularity (∼153m x ∼153m). We implemented the Wilcoxon rank-sum test with a <0.05 p-value threshold for each day since hot spotting policy to compare MODZCTA with any of the Zone's designation to those without designation. Our main outcomes are Average Median Percentage Time Home (AMPTH) and Device-Weighted Average Median Percentage Time Home (DWAMPTH) from SafeGraph Social Distancing Metrics summarized to MODZCTA boundaries. NYC residents from October 5, 2020, to December 31, 2020 (87 days total) using the 177 MODZCTA within NYC as geographic unit of analysis. For the AMPTH measurement, MODZCTAs with hot spotting Zone's designation had 84 days (95% of the days) with statistically significantly lower mobility than non-intervention MODZCTAs, and for the DWAMPTH measurement, 83 days (97% of the days) had statistically significantly lower mobility. 58 of the days had p-value<0.001 for AMPTH and 49 had p-value<0.001 for DWAMPTH, and only a minority of days had p-value>0.1 (2 days for AMPTH and 3 for DWAMPTH). Looking at individual boroughs, Brooklyn had 42 statistically significant days for AMPTH and 49 for DWAMPTH, while Queens had 12 statistically significant days for AMPTH and 7 for DWAMPTH. New York State’s micro-cluster focus Zones is associated with decreased mobility in high COVID-19 prevalence areas. Our study suggests that shutdowns targeted at small geographic areas may reduce mobility and thus can potentially help control COVID-19 spread.

Burden of schistosomiasis‐related mortality in Brazil: epidemiological patterns and spatial–temporal distribution, 2003–2018

To characterise the epidemiological patterns and the spatial-temporal distribution of schistosomiasis-related mortality in Brazil from 2003 to 2018. A national population-based ecological study that used official data from the Mortality Information System. The data included all deaths recorded in Brazil from 2003 to 2018 in which schistosomiasis was mentioned in the death certificate as an underlying or associated cause of death (multiple causes). The municipalities of residence were used as units of geographic analysis, and standardised and smoothed mortality rates (per 100000 inhabitants) were calculated using the local empirical Bayes method. Spatial autocorrelation was evaluated using global and local Moran indexes. To analyse the spatial dependence, the Getis-Ord G and Gi* statistics were used. During the study period, 18421113 deaths were recorded in Brazil. Schistosomiasis was mentioned in 11487 deaths (proportional mortality: 0.06%); for 8141 deaths (70.87%), it was listed as the underlying cause, and for 3346 deaths (29.13%), it was listed as an associated cause. The mean mortality rate was 0.38 deaths/100000 inhabitants. Individuals≥70years of age (RR: 115.34, 95% CI: 68.56-194.03) and residents in the Northeast region (RR: 10.81, 95% CI: 5.95-19.66) presented higher risks related to schistosomiasis. Municipalities with high mortality rates were identified in all regions, and high-risk clusters were found in municipalities located in the Northeast and Southeast regions of the country. Schistosomiasis remains an important cause of death in persistently endemic areas in Brazil, particularly in those with a high prevalence of the disease and a marked parasite load.

Geographic Variation in the Utilization of and Mortality After Emergency General Surgery Operations in the Northeastern and Southeastern United States.

To define geographic variations in emergency general surgery (EGS) care, we sought to determine how much variability exists in the rates of EGS operations and subsequent mortality in the Northeastern and Southeastern United States (US). While some geographic variations in healthcare are normal, unwarranted variations raise questions about the quality, appropriateness, and cost-effectiveness of care in different areas. Patients ≥18 years who underwent 1 of 10 common EGS operations were identified using the State Inpatient Databases (2011-2012) for 6 states, representing Northeastern (New York) and Southeastern (Florida, Georgia, Kentucky, North Carolina, Mississippi) US. Geographic unit of analysis was the hospital service area (HSA). Age-standardized rates of operations and in-hospital mortality were calculated and mapped. Differences in rates across geographic areas were compared using the Kruskal-Wallis test, and variance quantified using linear random-effects models. Variation profiles were tabulated via standardized rates of utilization and mortality to compare geographically heterogenous areas. 227,109 EGS operations were geospatially analyzed across the 6 states. Age-standardized EGS operation rates varied significantly by region (Northeast rate of 22.7 EGS operations per 10,000 in population versus Southeast 21.9; P < 0.001), state (ranging from 9.9 to 29.1; P < 0.001), and HSA (1.9-56.7; P < 0.001). The geographic variability in age-standardized EGS mortality rates was also significant at the region level (Northeast mortality rate 7.2 per 1000 operations vs Southeast 7.4; P < 0.001), state-level (ranging from 5.9 to 9.0 deaths per 1000 EGS operations; P < 0.001), and HSA-level (0.0-77.3; P < 0.001). Maps and variation profiles visually exhibited widespread and substantial differences in EGS use and morality. Wide geographic variations exist across 6 Northeastern and Southeastern US states in the rates of EGS operations and subsequent mortality. More detailed geographic analyses are needed to determine the basis of these variations and how they can be minimized.

The impact of population agglomeration of an area on its neighbors: evidence from the USA

Regions with high population agglomeration have always been important centers of growth throughout history. However, little is known about the economic spillovers an agglomerated region produces on its neighboring areas. In this paper, I look at the effect of growth of an agglomerated county on its surrounding non-agglomerated counties, by using the methods outlined in Qu and Lee (J Econom 184(2):209–232, 2015) and Qu et al. (Econom J 19(3):261–290, 2016). I use the US county as the geographic unit of analysis. The results show that the impact of is inverted U-shaped—at low levels of per capita income of an agglomerated county, growth has a positive impact on the neighboring non-agglomerated counties, relative to non-agglomerated counties that do not have any agglomerated counties nearby. However, as the agglomerated county gets richer, its relationship with the neighboring non-agglomerated county becomes negative, relative to the growth rate of a non-agglomerated county that has no agglomerated county nearby.

Towards a Model of Urban Studies Classification

Evolution of cities is a subject of research for over a hundred years in the organization of urban knowledge systems. Locating five key methodological approaches used by urban scholars and practitioners, this paper demonstrates different relationships between urban studies and classification. Five significant themes form the background of urban studies literature. The first theme sources and literature explore organizing urban materials into sources and literature with a unique dimension of spatiality. The second theme discusses three important facets: scale as a geographic unit of analysis and space as an abstract entity and system as a set of interdependent parts of urban places. The third theme, known as “other” urban, argued for the poor treatment of global south and how it builds inclusivity. The fourth theme, classification and retrieval, investigates the relationship between urban materials and user needs. The last theme, classification schemes, highlights subject treatment of urban in the existing library classification schemes. This paper concludes that the five themes discussed point to a model of urban studies classification. However, this model is not just concerned with urban methods, facets and formats, but explores how each theme interconnects with various sets of people-urbanists, practitioners and librarians-and through studying these actors, established boundaries of urban theories, urban librarianship and knowledge organization are crossed.

Geographic variation in cardiometabolic risk distribution: A cross-sectional study of 256,525 adult residents in the Illawarra-Shoalhaven region of the NSW, Australia.

Metabolic risk factors for cardiovascular disease (CVD) warrant significant public health concern globally. This study aims to utilise the regional database of a major laboratory network to describe the geographic distribution pattern of eight different cardiometabolic risk factors (CMRFs), which in turn can potentially generate hypotheses for future research into locality specific preventive approaches. A cross-sectional design utilising de-identified laboratory data on eight CMRFs including fasting blood sugar level (FBSL); glycated haemoglobin (HbA1c); total cholesterol (TC); high density lipoprotein (HDL); albumin creatinine ratio (ACR); estimated glomerular filtration rate (eGFR); body mass index (BMI); and diabetes mellitus (DM) status was used to undertake descriptive and spatial analyses. CMRF test results were dichotomised into 'higher risk' and 'lower risk' values based on existing risk definitions. Australian Census Statistical Area Level 1 (SA1) were used as the geographic units of analysis, and an Empirical Bayes (EB) approach was used to smooth rates at SA1 level. Choropleth maps demonstrating the distribution of CMRFs rates at SA1 level were produced. Spatial clustering of CMRFs was assessed using Global Moran's I test and Local Indicators of Spatial Autocorrelation (LISA). A total of 1,132,016 test data derived from 256,525 individuals revealed significant geographic variation in the distribution of 'higher risk' CMRF findings. The populated eastern seaboard of the study region demonstrated the highest rates of CMRFs. Global Moran's I values were significant and positive at SA1 level for all CMRFs. The highest spatial autocorrelation strength was found among obesity rates (0.328), and the lowest for albuminuria (0.028). LISA tests identified significant High-High (HH) and Low-Low (LL) spatial clusters of CMRFs, with LL predominantly in the less populated northern, central and southern regions of the study area. The study describes a range of CMRFs with different distributions in the study region. The results allow generation of hypotheses to test in future research concerning location specific population health approaches.

Ecological Research for Studies of Violence: A Methodological Guide.

Ecological research is important to the study of violence in communities. The phrases "ecological research" and "ecologic study" describe those research studies that use grouped or geographic units of analysis, such as zip codes, cities, or states. This type of research allows for the investigation of group-level effects and can be inexpensive and relatively quick to conduct if the researcher uses existing data. And, importantly, ecological studies are an efficient means for hypothesis generation prior to, and can be used to justify, costlier individual-level studies. Ecological research designs may be employed to study violence outcomes when the research question is at the population level, either for theoretical reasons, or when an exposure or intervention is at the population level, or when individual-level studies are not feasible; however, ecological research results must not be used to make individual-level inferences. This article will discuss reasons to conduct ecological-level research, guidelines for choosing the ecological unit of analysis, frequently used research designs, common limitations of ecological research, including the ecological fallacy, and issues to consider when using existing data.

Measuring Urban Greenspace Distribution Equity: The Importance of Appropriate Methodological Approaches

Urban greenspace can provide physical and mental health benefits to residents, potentially reducing health inequalities associated with socioeconomic deprivation. The distribution of urban greenspace is an important social justice issue, and consequently is increasingly studied. However, there is little consistency between studies in terms of methods and definitions. There is no consensus on what comprises the most appropriate geographic units of analysis or how to capture residents’ experience of their neighbourhood, leading to the possibility of bias. Several complementary aspects of distribution equity have been defined, yet few studies investigate more than one of these. There are also alternative methods for measuring each aspect of distribution. All of these can lead to conflicting conclusions, which we demonstrate by calculating three aspects of equity for two units of aggregation and three neighbourhood sizes for a single study area. We make several methodological recommendations, including taking steps to capture the relevant neighbourhood as experienced by residents accurately as possible, and suggest that using small-area aggregations may not result in unacceptable levels of information loss. However, a consideration of the local context is critical both in interpreting individual studies and understanding differing results.

Local Referral of High-Risk Pancreatectomy Patients to Improve Surgical Outcomes and Minimize Travel Burden

BackgroundReferring patients to high-quality hospitals for complex procedures may improve outcomes. This is most feasible within small geographic areas. However, access to specialized surgical procedures may be an implementation barrier. We sought to determine the availability of high-quality hospitals performing pancreatectomy and the potential benefit and travel burden of referral within small geographic areas. MethodsWe identified elderly Medicare beneficiaries undergoing pancreatectomy between 2012 and 2014. Hospitals were stratified into quintiles of quality based on postoperative complication rates. Patient risk was assessed by modeling the predicted risk of developing a postoperative complication. The geographic unit of analysis was Metropolitan Statistical Area (MSA). Hospitals were categorized into MSA by zip code. Travel distance was calculated using patient and hospital zip code. ResultsAmong high-risk patients, 40.7% received care at the lowest-quality hospitals even though 80% had a high-quality hospital in the same MSA. Shifting these patients from low- to high-quality hospitals would decrease serious complications from 46.6 to 21.9% (P < 0.001) and mortality from 10.9 to 8.9% (P = 0.047). Three quarters of high-risk patients treated at low-quality hospitals could reach a high-quality hospital by extending their travel < 5 miles, and nearly 60% traveled farther to a low-quality hospital than was necessary to reach a high-quality hospital. ConclusionsHigh-risk pancreatectomy patients often receive care at low-quality hospitals despite the availability of high-quality hospitals in the area or within an acceptable distance. Referral of high-risk patients to high-quality hospitals within small geographic areas may be an effective strategy to improve outcomes following pancreatic surgery.

Are We Serving the Most At-Risk Communities? Examining the Reach of a South Carolina Home Visiting Program.

In addition to individual-level characteristics, characteristics of the social and physical environments in which individuals reside may adversely impact health outcomes. Careful attention to the role of "place" can result in programs that successfully deliver services to those most at risk. This retrospective, cross-sectional study used geocoded residential addresses from 3090 households enrolled in a South Carolina (SC) home visiting program, 2013-2016, and corresponding years of data for maternal and child health outcomes obtained from vital records data. ZIP Code Tabulation Areas (ZCTAs) served as the primary geographic unit of analysis. ZCTAS with high volumes of birth or adverse maternal and child health outcomes for any of 10 indicators were flagged. Distribution of enrolled households across highest-risk ZCTAs was calculated. Of 379 ZCTAS with reported data, 152 had 8 or more risk flags. Of the 152 highest-risk ZCTAs, 33 also had high birth volumes. Fifty-seven of the 152 highest-risk ZCTAs had no enrollees; seven of the 33 highest-risk/highest-volume ZCTAS had no enrollees. Service delivery gaps existed despite a statewide, county-level needs assessment conducted prior to program implementation. This study suggests methods to identify service areas of need, as an ongoing effort toward program improvement.

Potential geographic "hotspots" for drug-injection related transmission of HIV and HCV and for initiation into injecting drug use in New York City, 2011-2015, with implications for the current opioid epidemic in the US.

ObjectiveWe identified potential geographic “hotspots” for drug-injecting transmission of HIV and hepatitis C virus (HCV) among persons who inject drugs (PWID) in New York City. The HIV epidemic among PWID is currently in an “end of the epidemic” stage, while HCV is in a continuing, high prevalence (> 50%) stage.MethodsWe recruited 910 PWID entering Mount Sinai Beth Israel substance use treatment programs from 2011–2015. Structured interviews and HIV/ HCV testing were conducted. Residential ZIP codes were used as geographic units of analysis. Potential “hotspots” for HIV and HCV transmission were defined as 1) having relatively large numbers of PWID 2) having 2 or more HIV (or HCV) seropositive PWID reporting transmission risk—passing on used syringes to others, and 3) having 2 or more HIV (or HCV) seronegative PWID reporting acquisition risk—injecting with previously used needles/syringes. Hotspots for injecting drug use initiation were defined as ZIP codes with 5 or more persons who began injecting within the previous 6 years.ResultsAmong PWID, 96% injected heroin, 81% male, 34% White, 15% African-American, 47% Latinx, mean age 40 (SD = 10), 7% HIV seropositive, 62% HCV seropositive. Participants resided in 234 ZIP codes. No ZIP codes were identified as potential hotspots due to small numbers of HIV seropositive PWID reporting transmission risk. Four ZIP codes were identified as potential hotspots for HCV transmission. 12 ZIP codes identified as hotspots for injecting drug use initiation.DiscussionFor HIV, the lack of potential hotspots is further validation of widespread effectiveness of efforts to reduce injecting-related HIV transmission. Injecting-related HIV transmission is likely to be a rare, random event. HCV prevention efforts should include focus on potential hotspots for transmission and on hotspots for initiation into injecting drug use. We consider application of methods for the current opioid epidemic in the US.

Local referral of pancreatectomy patients to improve surgical quality

Background: Referral of patients to high-quality hospitals (HQH) for complex procedures may improve outcomes. This is most feasible within small geographic areas, but access to specialized surgical procedures may be an implementation barrier. We sought to determine the availability of HQH performing pancreatectomy and the potential benefit of referral within small geographic areas. Methods: We identified pancreatectomy patients age ≥65 years in 2012–2013 Medicare claims data. Hospitals were grouped by risk-adjusted complication rates (HQH: best 2 quintiles; low- quality hospitals, LQH: worst 2 quintiles), and patients were risk-stratified by clinical factors. The geographic units of analysis were Metropolitan Statistical Areas (MSAs), each consisting of a population center ≥50,000 and the surrounding areas typical of commuting distances. Results: We analyzed data on 5579 patients treated at 646 hospitals. Of the 2402 patients (43%) who received care at 258 LQH, 74% had a HQH in their MSA. Patients treated at LQH were a median of 24 miles from a HQH. Patients treated in MSAs with only LQH were a median of 60 miles from a HQH in an adjacent MSA (Fig 1). A similar pattern was seen among high-risk patients; 71% were treated at LQH despite the presence of HQH in their MSA. High-risk patients treated at LQH were a median of 25 miles from a HQH. If high-risk patients traveled 25 miles to a HQH, post-pancreatectomy mortality would decrease from 7% to 4% (p = 0.0013) and morbidity would decrease by 48% (38% v 20%, p < 0.001). Conclusion: In small geographic areas pancreatectomy patients are often treated at LQH despite availability of HQH in the area or within an acceptable distance. Referral of patients, especially high-risk patients, to HQH within small geographic areas is a potentially effective strategy to improve outcomes of pancreatic surgery.

Spatiotemporal heterogeneity of malnutrition indicators in children under 5 years of age in Bangladesh, 1999-2011.

To examine changes in the spatial clustering of malnutrition in children under 5 years of age (under-5s) for the period 1999 to 2011 in Bangladesh. We used data from four nationally representative Demographic and Health Surveys (DHS) conducted in 1999-2000, 2004, 2007 and 2011 in Bangladesh involving a total of 24 211 under-5s located in 1661 primary sampling units (PSU; geographical unit of analysis) throughout Bangladesh. The prevalence of stunting (height/length-for-age Z-score <-2), underweight (weight-for-age Z-score <-2) and wasting (weight-for-height/length Z-score <-2) at each PSU site and for each survey year were estimated based on the WHO child growth standard. The extent of spatial clustering was quantified using semivariograms. Whole of Bangladesh. Children under 5 years of age. Our results demonstrate that in 1999-2000 most PSU throughout Bangladesh experienced stunting, underweight and wasting prevalence which exceeded the WHO thresholds. By 2011, this situation improved, although in two of the six divisions (Barisal and Sylhet) PSU still exhibited higher levels of malnutrition compared with other divisions of the country. The pattern of spatial clustering for stunting, underweight and wasting also changed between 1999 and 2011 both at national and sub-national (division) levels. We identified divisions where malnutrition indicators (stunting, underweight and wasting) remain highly clustered and other divisions where they are more widely spread in Bangladesh. This has important implications on how interventions for malnutrition need to be delivered (geographically targeted interventions v. random interventions) within each division of the country.

Nature and the City: changes for the first urban century in the United States

This panoramic view shows how are focused today the relationships between Nature and the City by research scholars and practitioners in North America. In the American context of an “endless city”, it develops four key ideas for a better approach to urban ecosystems: urban ecology, sustainability, new regionalism and landscape urbanism. Urban ecology has emerged as an interdisciplinary approach for understanding the “drivers, patterns, processes, and outcomes” associated with urban and urbanizing landscapes. With the leadership of several American cities, as New York City, Chicago, Seattle and Portland, urban greening efforts based on principles of sustainability are developed. The new perspectives on regionalism are evident in different efforts associated with the megaregion/megapolitan concept: a new geographic unit of analysis and a new scale for planning. This new regionalism represents a movement led by architects and planners involving geographers, demographers, and policy makers. Finally, landscape urbanism is a more design-based approach. Instead of viewing nature in the city, we have begun to understand the ecology of cities: the urban systems are ecosystems. As a result, “nature cannot be used as exterior decoration, but rather as integral to the health and resiliency of human settlement”.