Features of alcohol advertisements across five urban slums in Kampala, Uganda: pilot testing a container-based approach.

BACKGROUND: Despite the high prevalence of alcohol use and marketing in many settings across sub-Saharan Africa, few studies have systematically sought to assess alcohol marketing exposure, particularly in vulnerable areas such as urban slums where alcohol is often highly prevalent but where educational programs and alcohol prevention messages are scarce. OBJECTIVE: To pilot test the development and implementation of environmental scans of alcohol advertisements in five urban slums across different areas of Kampala, Uganda: Bwaise, Kamwokya, Makindye, Nakulabye, and Nateete. METHODS: Each of the five scans was conducted in geographical circles, within a 500-m radius of a Uganda Youth Development Link (UYDEL) drop-in Center using a container-based approach. Using a Garmin GPS with photo capabilities and a tablet for data entry, teams of at least two trained researchers walked the main roads within the target area and gathered information about each alcohol advertisement including its location, type, size, and placement and other characteristics. Data with the GPS coordinates, photos and descriptive details of the adverts were merged for analyses. RESULTS: A total of 235 alcohol adverts were found across all five data collection sites reflecting 32 different brands. The majority of the adverts (85.8%) were smaller and medium sizes placed by restaurants and bars, stores and kiosks, and liquor stores. The most frequently noted types of alcohol in the adverts were spirits (50.6%) and beer (30.6%). RECOMMENDATIONS: The pilot test of the methodology we developed indicated that implementation was feasible, although challenges were noted. Since monitoring alcohol marketing is key for addressing underage alcohol use and harm, the advantages and disadvantages of the approach we developed are discussed. Future research needs to strengthen and simplify strategies for monitoring alcohol marketing in low-resource settings such as urban slums which have unique features that need to be considered. Meanwhile, the findings may yield valuable information for stakeholders and to guide intervention developments and alcohol marketing policy to protect youth.

The Human Immunodeficiency Virus Endemic: Maintaining Disease Transmission in At-Risk Urban Areas.

OBJECTIVES: A study of network relationships, geographic contiguity, and risk behavior was designed to test the hypothesis that all 3 are required to maintain endemicity of human immunodeficiency virus (HIV) in at-risk urban communities. Specifically, a highly interactive network, close geographic proximity, and compound risk (multiple high-risk activities with multiple partners) would be required. METHODS: We enrolled 927 participants from two contiguous geographic areas in Atlanta, GA: a higher-risk area and lower-risk area, as measured by history of HIV reporting. We began by enrolling 30 "seeds" (15 in each area) who were comparable in their demographic and behavioral characteristics, and constructed 30 networks using a chain-link design. We assessed each individual's geographic range; measured the network characteristics of those in the higher and lower-risk areas; and measured compound risk as the presence of two or more (of 6) major risks for HIV. RESULTS: Among participants in the higher-risk area, the frequency of compound risk was 15%, compared with 5% in the lower-risk area. Geographic cohesion in the higher-risk group was substantially higher than that in the lower-risk group, based on comparison of geographic distance and social distance, and on the extent of overlap of personal geographic range. The networks in the 2 areas were similar: both areas show highly interactive networks with similar degree distributions, and most measures of network attributes were virtually the same. CONCLUSIONS: Our original hypothesis was supported in part. The higher and lower-risk groups differed appreciably with regard to risk and geographic cohesion, but were substantially the same with regard to network properties. These results suggest that a "minimum" network configuration may be required for maintenance of endemic transmission, but a particular prevalence level may be determined by factors related to risk, geography, and possibly other factors.

Improvement of Geographic Disparities: Amelioration or Displacement?

Progression of geographic disparities in social determinants of health is a global concern. Using an Urban Health Index (UHI) approach, we proposed a framework of examining the change of geographic disparities in social determinants in small areas. Using the City of Atlanta in Georgia (USA) as a case study, we standardized six census-based social determinant indicators in 2000 and in 2010, respectively, and calculated their geometric mean to assign each census tract a UHI value for 2000 and for 2010. We then evaluated the temporal change of the UHIs in relation to the demographic changes using spatial and statistical methods. We found that Atlanta experienced an improvement in social determinant status and a reduction of disparities in the 10 years. The areas that experienced improvement, however, underwent demographic changes as well. This analysis provides support for displacement, rather than improvement, as the underlying factor for apparent change in geographic disparities. Findings suggest the importance of local evaluation for future policies to reduce disparities in cities.

Mortality rates and the causes of death related to diabetes mellitus in Shanghai Songjiang District: an 11-year retrospective analysis of death certificates.

BACKGROUND: China is one of the countries with the highest prevalence of diabetes in the world. We analysed all the death certificates mentioning diabetes from 2002 to 2012 in Songjiang District of Shanghai to estimate morality rates and examine cause of death patterns. METHODS: Mortality data of 2654 diabetics were collected from the database of local CDC. The data set comprises all causes of death, contributing causes and the underlying cause, thereby the mortality rates of diabetes and its specified complications were analysed. RESULTS: The leading underlying causes of death were various cardiovascular diseases (CVD), which collectively accounted for about 30% of the collected death certificates. Diabetes was determined as the underlying cause of death on 28.7%. The trends in mortality showed that the diabetes related death rate increased about 1.78 fold in the total population during the 11-year period, and the death rate of diabetes and CVD comorbidity increased 2.66 fold. In all the diabetes related deaths, the proportion of people dying of ischaemic heart disease or cerebrovascular disease increased from 18.0% in 2002 to 30.5% in 2012. But the proportions attributed directly to diabetes showed a downtrend, from 46.7-22.0%. CONCLUSIONS: The increasing diabetes related mortality could be chiefly due to the expanding prevalence of CVD, but has nothing to do with diabetes as the underlying cause. Policy makers should pay more attention to primary prevention of diabetes and on the prevention of cardiovascular complications to reduce the burden of diabetes on survival.

Urban health indicators and indices--current status.

Though numbers alone may be insufficient to capture the nuances of population health, they provide a common language of appraisal and furnish clear evidence of disparities and inequalities. Over the past 30 years, facilitated by high speed computing and electronics, considerable investment has been made in the collection and analysis of urban health indicators, environmental indicators, and methods for their amalgamation. Much of this work has been characterized by a perceived need for a standard set of indicators. We used publication databases (e.g. Medline) and web searches to identify compilations of health indicators and health metrics. We found 14 long-term large-area compilations of health indicators and determinants and seven compilations of environmental health indicators, comprising hundreds of metrics. Despite the plethora of indicators, these compilations have striking similarities in the domains from which the indicators are drawn--an unappreciated concordance among the major collections. Research with these databases and other sources has produced a small number of composite indices, and a number of methods for the amalgamation of indicators and the demonstration of disparities. These indices have been primarily used for large-area (nation, region, state) comparisons, with both developing and developed countries, often for purposes of ranking. Small area indices have been less explored, in part perhaps because of the vagaries of data availability, and because idiosyncratic local conditions require flexible approaches as opposed to a fixed format. One result has been advances in the ability to compare large areas, but with a concomitant deficiency in tools for public health workers to assess the status of local health and health disparities. Large area assessments are important, but the need for small area action requires a greater focus on local information and analysis, emphasizing method over prespecified content.

A flexible urban health index for small area disparities.

Available urban health metrics focus primarily on large area rankings. Less has been done to develop an index that provides information about level of health and health disparities for small geographic areas. Adopting a method used by the Human Development Index, we standardized indicators for small area units on a (0, 1) interval and combined them using their geometric mean to form an Urban Health Index (UHI). Disparities were assessed using the ratio of the highest to lowest decile and measurement of the slope of the eight middle deciles (middle; 80 %) of the data. We examined the sensitivity of the measure to weighting, to changes in the method, to correlation among indicators, and to substitution of indicators. Using seven health determinants and applying these methods to the 128 census tracts in the city of Atlanta, USA, we found a disparity ratio of 5.92 and a disparity slope of 0.54, suggesting substantial inequality and heterogeneity of risk. The component indicators were highly correlated; their systematic removal had a small effect on the results. Except in extreme cases, weighting had a little effect on the rankings. A map of Atlanta census tracts exposed a swath of high disparity. UHI rankings, ratio, and slope were resistant to alteration in composition and to non-extreme weighting schemes. This empirical evaluation was limited to a single realization, but suggests that a flexible tool, whose method rather than content is standardized, may be of use for local evaluation, for decision making, and for area comparison.

Case cluster shifting and contaminant source as determinants of melioidosis in Taiwan.

OBJECTIVES: To assess the geographical distribution of melioidosis contamination sources and the association between the location of melioidosis cases and positive sampling sites for Burkholderia pseudomallei in Taiwan. METHODS: Data on the location of melioidosis cases from 2002 to 2011 were combined with the geographical distribution of B. pseudomallei as indicated by the detection of specific flagella gene products measured from 2005 to 2011. Temporal and spatial analyses were used to determine the incidence, cluster shifts and associations between the two datasets. RESULTS: Melioidosis cases clustered in two 'hot-spot' areas with incidence rates that were significantly higher than in neighbouring towns. The incidence rates in the northern area gradually decreased, while the rates in the southern area increased and were temporally associated with the appearance of B. pseudomallei-specific flagella genes in water samples. CONCLUSIONS: Melioidosis hot-spot areas were present in Taiwan. Water contaminated with B. pseudomallei serves as a potential transmission vehicle and is correlated with an increase in melioidosis cases; this correlation was stronger than that for B. pseudomallei-contaminated soil.

Neighborhood characteristics of low radon testing activities: A longitudinal study in Atlanta, Georgia, United States.

Radon testing remains low even nationwide although its exposure is the leading cause of lung cancer among non-smokers. Little has been done to examine the neighborhood characteristics with low testing prevalence. This study investigated the associations between indoor radon testing and neighborhood characteristics in an urban environment with the highest Radon potential. A total of 25 years (1990-2015) of radon tests (n = 6355) were pooled from public and private sources in DeKalb County, Georgia, United States. Neighborhoods were characterized using racial residential segregation for African Amercians in addition to other social indicators. The associations between neighborhood characteristics and radon testing rates were evaluated using Ordinary Least Squares and Spatial Regression Models, respectively. Results show that the testing rates were lower than 6.5% over the 25 years. Summers followed by early springs experienced more tests than the other seasons. Areas of low testing rates (≤1.55%) spatially matches the mostly segregated neighborhoods. Residential segregation expanded in the 25 years and was significantly correlated (P value < 0.05) with low testing rates, even after other social indicators were controlled. Associations with the other social indicators, such as income or education, were weaker. Concertedly identifying the culturally relevant interventions in segregated communities is necessary to reduce and eliminate threats from environmental radon.

Association of Race and Area Deprivation With Breast Cancer Survival Among Black and White Women in the State of Georgia.

Importance: Increasing evidence suggests that low socioeconomic status and geographic residence in disadvantaged neighborhoods contribute to disparities in breast cancer outcomes. However, little epidemiological research has sought to better understand these disparities within the context of location. Objective: To examine the association between neighborhood deprivation and racial disparities in mortality among Black and White patients with breast cancer in the state of Georgia. Design, Setting, and Participants: This population-based cohort study collected demographic and geographic data from patients diagnosed with breast cancer between January 1, 2004, and February 11, 2020, in 3 large health care systems in Georgia. A total of 19 580 patients with breast cancer were included: 12 976 from Piedmont Healthcare, 2285 from Grady Health System, and 4319 from Emory Healthcare. Data were analyzed from October 2, 2020, to August 11, 2022. Exposures: Area deprivation index (ADI) scores were assigned to each patient based on their residential census block group. The ADI was categorized into quartile groups, and associations between ADI and race and ADI × race interaction were examined. Main Outcomes and Measures: Cox proportional hazards regression models were used to compute hazard ratios (HRs) and 95% CIs associating ADI with overall mortality by race. Kaplan-Meier curves were used to visualize mortality stratified across racial and ADI groups. Results: Of the 19 580 patients included in the analysis (mean [SD] age at diagnosis, 58.8 [13.2] years), 3777 (19.3%) died during the course of the study. Area deprivation index contributed differently to breast cancer outcomes for Black and White women. In multivariable-adjusted models, living in a neighborhood with a greater ADI (more deprivation) was associated with increased mortality for White patients with breast cancer; compared with the ADI quartile of less than 25 (least deprived), increased mortality HRs were found in quartiles of 25 to 49 (1.22 [95% CI, 1.07-1.39]), 50 to 74 (1.32 [95% CI, 1.13-1.53]), and 75 or greater (1.33 [95% CI, 1.07-1.65]). However, an increase in the ADI quartile group was not associated with changes in mortality for Black patients with breast cancer (quartile 25 to 49: HR, 0.81 [95% CI, 0.61-1.07]; quartile 50 to 74: HR, 0.91 [95% CI, 0.70-1.18]; and quartile ≥75: HR, 1.05 [95% CI, 0.70-1.36]). In neighborhoods with an ADI of 75 or greater, no racial disparity was observed in mortality (HR, 1.11 [95% CI, 0.92-1.36]). Conclusions and Relevance: Black women with breast cancer had higher mortality than White women in Georgia, but this disparity was not explained by ADI: among Black patients, low ADI was not associated with lower mortality. This lack of association warrants further investigation to inform community-level approaches that may mitigate the existing disparities in breast cancer outcomes in Georgia.

Space-Time Surveillance of Negative Emotions After Consecutive Terrorist Attacks in London.

Terrorist attacks pose significant threats to mental health. There is dearth information about the impact of consecutive terrorist attacks on space-time concentrations of emotional reactions. This study collected (1) Twitter data following the two terrorist attacks in London in March and June of 2017, respectively, and (2) deprivation data at small areal levels in the United Kingdom. The space-time permutation model was used to detect the significant clusters of negative emotions, including fear, sadness, and anger in tweets. Logistic regression models were used to examine the social deprivation of communities associated with negative tweeting. The results reported two significant clusters after the March attack, one was in London, ten days after the attack, and the other was far from the attack site between Manchester and Birmingham, three days after the attack. Attention to the reoccurring attack in June diminished quickly. The socially deprived communities experienced double disadvantage-sending fewer tweets but expressing more negative emotions than their counterparts. The findings suggest that terrorism can affect public emotions far and broad. There is a potential for surveillance to rapidly identify geographically concentrated emotions after consecutive or prolonged disasters using social media data.

Confluent impact of housing and geology on indoor radon concentrations in Atlanta, Georgia, United States.

Radon is a naturally released radioactive carcinogenic gas. To estimate radon exposure, studies have examined various risk factors, but limited information exists pertaining to the confluent impact of housing characteristics and geology. This study evaluated the efficacy of housing and geological characteristics to predict radon risk in DeKalb County, Georgia, USA. Four major types of data were used: (1) three databases of indoor radon concentrations (n = 6757); (2) geologic maps of rock types and fault zones; (3) a database of 402 in situ measurements of gamma emissions, and (4) two databases of housing characteristics. The Getis-Ord method was used to delineate hot spots of radon concentrations. Empirical Bayesian Kriging was used to predict gamma radiation at each radon test site. Chi-square tests, bivariate correlation coefficients, and logistic regression were used to examine the impact of geological and housing factors on radon. The results showed that indoor radon levels were more likely to exceed the action level-4 pCi/L (148 Bq/m3) designated by the U.S. Environmental Protection Agency-in fault zones, were significantly positively correlated to gamma readings, but significantly negatively related to the presence of a crawlspace foundation and its combination with a slab. The findings suggest that fault mapping and in situ gamma ray measurements, coupled with analysis of foundation types and delineation of hot spots, may be used to prioritize areas for radon screening.

Spatial variations in the incidence of breast cancer and potential risks associated with soil dioxin contamination in Midland, Saginaw, and Bay Counties, Michigan, USA.

BACKGROUND: High levels of dioxins in soil and higher-than-average body burdens of dioxins in local residents have been found in the city of Midland and the Tittabawassee River floodplain in Michigan. The objective of this study is threefold: (1) to evaluate dioxin levels in soils; (2) to evaluate the spatial variations in breast cancer incidence in Midland, Saginaw, and Bay Counties in Michigan; (3) to evaluate whether breast cancer rates are spatially associated with the dioxin contamination areas. METHODS: We acquired 532 published soil dioxin data samples collected from 1995 to 2003 and data pertaining to female breast cancer cases (n = 4,604) at ZIP code level in Midland, Saginaw, and Bay Counties for years 1985 through 2002. Descriptive statistics and self-organizing map algorithm were used to evaluate dioxin levels in soils. Geographic information systems techniques, the Kulldorff's spatial and space-time scan statistics, and genetic algorithms were used to explore the variation in the incidence of breast cancer in space and space-time. Odds ratio and their corresponding 95% confidence intervals, with adjustment for age, were used to investigate a spatial association between breast cancer incidence and soil dioxin contamination. RESULTS: High levels of dioxin in soils were observed in the city of Midland and the Tittabawassee River 100-year floodplain. After adjusting for age, we observed high breast cancer incidence rates and detected the presence of spatial clusters in the city of Midland, the confluence area of the Tittabawassee, and Saginaw Rivers. After accounting for spatiotemporal variations, we observed a spatial cluster of breast cancer incidence in Midland between 1985 and 1993. The odds ratio further suggests a statistically significant (alpha = 0.05) increased breast cancer rate as women get older, and a higher disease burden in Midland and the surrounding areas in close proximity to the dioxin contaminated areas. CONCLUSION: These findings suggest that increased breast cancer incidences are spatially associated with soil dioxin contamination. Aging is a substantial factor in the development of breast cancer. Findings can be used for heightened surveillance and education, as well as formulating new study hypotheses for further research.

Hotspots of road traffic crashes in a redeveloping area of Shanghai.

To identify high-risk locations (hotspots) of road traffic crashes (RTC) in a redeveloping area of Shanghai, for formulating relevant countermeasures in similar areas. After geocoding the crash locations on electronic map, assessment of spatial clustering of accidents and hotspots spatial densities was conducted following Moran's I method, the kernel density estimation, the Ripley's K-function and the network-based kernel density estimation (NKDE). A total of 21,679 RTC incidents resulting in 24,147 victims were recorded from 2010 to 2012. RTCs tended to occur among male (81.8%) aged 20-49 years old (84.9%) riding buses (60.1%) or electric bikes (16.1%) in working time (15%). The network spatial analysis pinpointed the hotspots of RTC at the street level in the Songjiang new urban area, and more RTCs occurred at road intersections than on road segments. Findings from this research may help the authorities develop efficient programmes to target high-risk locations and specific vulnerable populations.

Mapping the Hidden Hazards: Community-Led Spatial Data Collection of Street-Level Environmental Stressors in a Degraded, Urban Watershed.

We utilized a participatory mapping approach to collect point locations, photographs, and descriptive data about select built environment stressors identified and prioritized by community residents living in the Proctor Creek Watershed, a degraded, urban watershed in Northwest Atlanta, Georgia. Residents (watershed researchers) used an indicator identification framework to select three watershed stressors that influence urban livability: standing water, illegal dumping on land and in surface water, and faulty stormwater infrastructure. Through a community⁻university partnership and using Geographic Information Systems and digital mapping tools, watershed researchers and university students designed a mobile application (app) that enabled them to collect data associated with these stressors to create a spatial narrative, informed by local community knowledge, that offers visual documentation and representation of community conditions that negatively influence the environment, health, and quality of life in urban areas. By elevating the local knowledge and lived experience of community residents and codeveloping a relevant data collection tool, community residents generated fine-grained, street-level, actionable data. This process helped to fill gaps in publicly available datasets about environmental hazards in their watershed and helped residents initiate solution-oriented dialogue with government officials to address problem areas. We demonstrate that community-based knowledge can contribute to and extend scientific inquiry, as well as help communities to advance environmental justice and leverage opportunities for remediation and policy change.

Measuring the Impact of Environment on the Health of Large Cities.

The relative significance of indicators and determinants of health is important for local public health workers and planners. Of similar importance is a method for combining and evaluating such markers. We used a recently developed index, the Urban Health Index (UHI), to examine the impact of environmental variables on the overall health of cities. We used the UHI to rank 57 of the world’s largest cities (based on population size) in low- and middle-income countries. We examined nine variables in various combinations that were available from the Demographic and Health Surveys conducted in these countries. When arranged in ascending order, the distribution of UHIs follows the previously described pattern of gradual linear increase, with departures at each tail. The rank order of cities did not change materially with the omission of variables about women’s health knowledge or childhood vaccinations. Omission of environmental variables (a central water supply piped into homes, improved sanitation, and indoor solid fuel use) altered the rank order considerably. The data suggest that environmental indicators, measures of key household level risk to health, may play a vital role in the overall health of urban communities.

The use of gamma-survey measurements to better understand radon potential in urban areas.

Accounting for as much as 14% of all lung cancers worldwide, cumulative radon progeny exposure is the leading cause of lung cancer among never-smokers both internationally and in the United States. To understand the risk of radon progeny exposure, studies have mapped radon potential using aircraft-based measurements of gamma emissions. However, these efforts are hampered in urban areas where the built environment obstructs aerial data collection. To address part of this limitation, this study aimed to evaluate the effectiveness of using in situ gamma readings (taken with a scintillation probe attached to a ratemeter) to assess radon potential in an urban environment: DeKalb County, part of the Atlanta metropolitan area, Georgia, USA. After taking gamma measurements at 402 survey sites, empirical Bayesian kriging was used to create a continuous surface of predicted gamma readings for the county. We paired these predicted gamma readings with indoor radon concentration data from 1351 residential locations. Statistical tests showed the interpolated gamma values were significantly but weakly positively related with indoor radon concentrations, though this relationship is decreasingly informative at finer geographic scales. Geology, gamma readings, and indoor radon were interrelated, with granitic gneiss generally having the highest gamma readings and highest radon concentrations and ultramafic rock having the lowest of each. Our findings indicate the highest geogenic radon potential may exists in the relatively undeveloped southeastern part of the county. It is possible that in situ gamma, in concert with other variables, could offer an alternative to aerial radioactivity measurements when determining radon potential, though future work will be needed to address this project's limitations.

A Pilot Study to Examine Exposure to Residential Radon in Under-Sampled Census Tracts of DeKalb County, Georgia, in 2015.

While DeKalb County, Georgia, offers free radon screening for all eligible residents, portions of the county remain relatively under-sampled. This pilot study focused on 10% of the census tracts in the county with the lowest proportion of radon testing; most were in southern DeKalb County. In total, 217 households were recruited and homes were tested for indoor radon concentrations on the lowest livable floor over an eight-week period from March-May 2015. Tract-level characteristics were examined to understand the differences in socio-demographic and economic factors between the pilot study area and the rest of the county. The pilot study tracts had a higher proportion of African Americans compared to the rest of DeKalb County (82% versus 47%). Radon was detected above 11.1 Bq/m³ (0.3 pCi/L) in 73% of the indoor samples and 4% of samples were above 148 Bq/m³ (4 pCi/L). Having a basement was the strongest predictive factor for detectable and hazardous levels of radon. Radon screening can identify problems and spur homeowners to remediate but more research should be done to identify why screening rates vary across the county and how that varies with radon levels in homes to reduce radon exposure.

Spatiotemporal distributions of reported cases of the avian influenza H5N1 (bird flu) in Southern China in early 2004.

This study investigates spatiotemporal distributions of reported cases of the avian influenza H5N1 (bird flu) in Southern China in early 2004. Forty-nine cases of the avian influenza H5N1 covering a 6-week period (January 19, 2004, through March 9, 2004) were compiled from the Chinese Ministry of Agriculture and the World Health Organization. Geographic information systems (GIS) techniques combined with statistical techniques were used to analyze the spatiotemporal variation of reported cases of avian influenza. Using Oden's direction method, we also explored the spatiotemporal interaction of individual-level avian influenza cases during the study duration. The peak period (temporal clustering) for the epidemiological avian influenza outbreak occurred between the third and fourth weeks. Although we observed a major northeast-southwest distribution of the avian influenza H5N1 cases, there was no significant spatiotemporal association in average "direction of advance" of these cases. The directional finding is very consistent with the major migratory bird routes in East Asia, but owing to weak surveillance and reporting systems in the region, the study findings warrant further evaluation.

A cross-sectional and spatial analysis of the prevalence of multimorbidity and its association with socioeconomic disadvantage in South Africa: A comparison between 2008 and 2012.

This study utilised data from the National Income Dynamics Study, a longitudinal study with a sample of approximately 28 000 people, to investigate the cross-sectional and spatial distribution of multimorbidity and the association with socioeconomic disadvantage in South Africa for 2008 and 2012. Multimorbidity increased in prevalence from 2.73% to 2.84% in adults between 2008 and 2012 and was associated with age, socioeconomic deprivation, obesity and urban areas. Hypertension was found frequently coexisting with diabetes. Spatial analysis showed clusters (hot spots) of higher multimorbidity prevalence in parts of KwaZulu-Natal and the Eastern Cape, which compared with the socioeconomic disadvantage spatial pattern. Although these results were limited to a district level analysis, this study has provided a platform for future local level research and has provided insight into the socioeconomic determinants of disease multimorbidity within a developing country.

Evidence-based community consultation for traumatic brain injury.

OBJECTIVES: The objective was to determine if geospatial techniques can be used to inform targeted community consultation (CC) and public disclosure (PD) for a clinical trial requiring emergency exception from informed consent (EFIC). METHODS: Data from January 2007 to December 2009 were extracted from a Level I trauma center's trauma database using the National Trauma Registry of the American College of Surgeon (NTRACS). Injury details, demographics, geographic codes, and clinical data necessary to match core elements of the clinical trial inclusion criteria (Glasgow Coma Scale [GCS] 3-12 and blunt head injury) were collected on all patients. Patients' home zip codes were geocoded to compare with population density and clustering analysis. RESULTS: Over a 2-year period, 179 patients presented with moderate to severe traumatic brain injury (TBI). Mapping the rate and frequency of TBI patients presenting to the trauma center delineated at-risk populations for moderate to severe head injury. Four zip codes had higher incidences of TBI than the rest, with one zip code having a very high rate of 80 per 100,000 population. CONCLUSIONS: Geospatial techniques and hospital data records can be used to characterize potential subjects and delineate a high-risk population to inform directed CC and public disclosure strategies.