Jornada de activos de Distrito Centro: compartiendo activos de manera práctica / Conference of Central District health assets: sharing asset: sharing assets in a practical way

INTRODUCCIÓN: El mapeo de activos en salud es un proceso comunitario para la ubicación territorial de activos para la salud, siendo un activo «cualquier factor (o recurso) que mejora la capacidad de las personas, grupos, comunidades, poblaciones, sistemas sociales e instituciones para mantener y sostener la salud y el bienestar, y que les ayuda a reducir las desigualdades en salud». OBJETIVOS: Visibilizar el trabajo realizado en el Proceso de Activos de Salud del Grupo Motor del Distrito Centro de Madrid y compartir conocimientos entre los diferentes agentes clave que han participado en distintas fases de este proceso. Generar como red comunitaria, estrategias prácticas para la recomendación de activos para la salud en la intervención sociosanitaria. MÉTODOS: Desde el Grupo Motor de Mapeo de Activos para la Salud del Distrito Centro de Madrid (formado por 26 entidades) se ha diseñado y desarrollado una jornada/encuentro para visibilizar los activos para la salud identificados en los últimos 2 años. RESULTADOS: Asistieron 35 profesionales del distrito de vertiente social, sanitaria y sociosanitaria y la evaluación de la jornada que hicieron las personas asistentes fue altamente satisfactoria. DISCUSIÓN: Esta jornada fue el resultado de visibilizar el trabajo realizado desde mayo de 2017, que es cuando se comenzó el Proceso de Mapeo de Activos para la Salud del Distrito Centro. Visibilizar esta tarea se tradujo en un conocimiento en profundidad del proceso de mapeo del distrito y de la metodología de activos, con lo que se consiguió un mayor empoderamiento de las personas asistentes

INTRODUCTION: Mapping of health assets is a community process for locating health assets territorially. Health assets are factors (or resources) that improve the abilities of individuals, groups, communities, populations, social systems and institutions to maintain and sustain health and welfare and help them reduce health inequality. OBJECTIVES: To raise awareness the work performed by the health assets process of the Central District Steering Group of Madrid. Sharing knowledge among different key actors involved in the Central District mapping process at different stages. Creation as a Community Network of practical strategies for recommending health assets for social and health intervention. METHODS: From the Health Asset Mapping Steering Group of the Central District (comprised of 26 entities) a conference/meeting to enhance the visibility of identified health assets has been designed and developed in the last two years. RESULTS: A total of 35 social, health and socio-health professionals from the district attended and the meeting evaluation by attendees was highly satisfactory. DISCUSSION: This meeting has been the result of enhancing visibility of work performed since May 2017, which is when the Central District Health Asset Process began. This visibility led to in-depth knowledge of the District's Health Asset Process and asset methodology, which attained a greater empowerment of attendees

Mortalidad atribuida a telangiectasia hemorrágica hereditaria y variabilidad geográfica en España (1981-2016) / Mortality attributed to hereditary haemorrhagic telangiectasia and geographical variability in Spain (1981-2016)

OBJETIVO: Conocer la mortalidad directamente atribuida a la telangiectasia hemorrágica hereditaria (THH) en España, su tendencia temporal y la posible variabilidad geográfica. MÉTODO: El total de los fallecidos por THH de base poblacional se obtuvo del Instituto Nacional de Estadística, seleccionando los códigos 448.0 (CIE 9-MC, 1981-1998) y I78.0 (CIE 10, 1999-2016) como causa básica de defunción. Se calcularon las tasas de mortalidad específicas y ajustadas por edad para cada sexo, las razones de mortalidad estandarizadas (RME) por provincia y comarca, y las RME suavizadas. RESULTADOS: Se identificaron 327 fallecimientos por THH (el 49,5% eran mujeres), siendo la mortalidad más alta a los 80-84 años en los hombres (0,220 por 100.000 habitantes) y a los 75-79 años en las mujeres (0,147 por 100.000 habitantes). No se detectaron cambios temporales entre 1981 y 2016. Las provincias de Navarra, Cantabria, Guipúzcoa, Pontevedra y Las Palmas presentaron un riesgo significativamente superior con respecto a lo esperado para el total nacional, así como las comarcas de Monte Sur (Ciudad Real) y Ripollès (Girona). CONCLUSIONES: Este trabajo ha permitido identificar algunas regiones con mayor riesgo de defunción por THH, si bien se desconoce si estas diferencias se asocian a la distribución de los tipos THH1 y THH2, por lo que son necesarios estudios posteriores para profundizar en las causas de la variabilidad geográfica. Estos hallazgos complementan la información proporcionada por otros estudios y registros, además de ser útiles para la planificación sanitaria

OBJECTIVE: To identify the mortality directly attributed to hereditary haemorrhagic telangiectasia (HHT) in Spain, and to analyze its time trends and geographic variability. METHOD: Population-based deaths due to HHT were selected from the Spanish National Statistics Institute: codes 448.0 (ICD-9, 1981-1998) and I78.0 (ICD-10, 1999-2016) as the basic cause of death. Specific and age-adjusted mortality rates were calculated by sex, as well as standardized mortality ratios (SMR) by province and district, and smoothed SMR. RESULTS: We identified 327 deaths attributed to HHT (49.5% women), with the highest mortality at 80-84 years in men (0.220 per 100,000 inhabitants) and at 75-79 years in women (0.147 per 100,000 inhabitants). Age-adjusted mortality rates did not show any significant time trend between 1981 and 2016 in Spain. The provinces of Navarra, Cantabria, Guipúzcoa, Pontevedra and Las Palmas had higher than expected mortality, as well as the regions of Monte Sur (Ciudad Real) and Ripollès (Girona). CONCLUSIONS: This study has identified some regions with higher risk of death due to HHT in Spain. It is unknown whether these differences are associated with the distribution of types HHT1 and HHT2, and further studies will be necessary to know the determinants of this geographical variability. These findings are useful to complement the information provided by other studies and registries, and for health planning

Extending multilevel spatial models to include spatially varying coefficients.

Multilevel models have long been used by health geographers working on questions of space, place, and health. Similarly, health geographers have pursued interests in determining whether or not the effect of an exposure on a health outcome varies spatially. However, relatively little work has sought to use multilevel models to explore spatial variability in the effects of a contextual exposure on a health outcome. Methodologically, extending multilevel models to allow intercepts and slopes to vary spatially is straightforward. The purpose of this paper, therefore, is to show how multilevel spatial models can be extended to include spatially varying covariate effects. We provide an empirical example on the effect of agriculture on malaria risk in children under 5 years of age in the Democratic Republic of Congo.

How context matters: Demonstrating microgeographical differences in social capital and its implications for mental wellbeing in pregnancy with a novel bubble diagram technique.

There has been limited exploration of social capital at the contextual level in relation to maternal health, and in particular with the "obstetric transition" and associated mental health problems. In the North Central Province of Sri Lanka, with socio-culturally diverse communities, and a recent history of major conflict, the leading cause of maternal death is suicide. The objective of this study was to identify contextual patterns of social capital constructs that lead to poor maternal mental wellbeing, using a novel bubble visualisation technique, to demonstrate the use of data derived from qualitative approaches. We conducted a qualitative study of pregnant women based on diary entries (n = 41) and interviews (n = 38) in eight different communities of the Anuradhapura district of Sri Lanka. Bubble diagrams were constructed to visualize each context using the frequency and weight of responses given in diaries. Marital, family and neighbourhood cohesion were not homogenous in the district and the bubble diagrams displayed clear microgeographical patterns in which women living in specific communities had poorer mental wellbeing. Such techniques can be used to convey complex social capital implications in digestible way for policy makers and planners to enact locally specific strategies addressing health inequalities.

Describing mortality trends for major cancer sites in 133 intermediate regions of Brazil and an ecological study of its causes.

BACKGROUND: In Brazil, 211 thousand (16.14%) of all death certificates in 2016 identified cancer as the underlying cause of death, and it is expected that around 320 thousand will receive a cancer diagnosis in 2019. We aimed to describe trends of cancer mortality from 1996 to 2016, in 133 intermediate regions of Brazil, and to discuss macro-regional differences of trends by human development and healthcare provision. METHODS: This ecological study assessed georeferenced official data on population and mortality, health spending, and healthcare provision from Brazilian governmental agencies. The regional office of the United Nations Development Program provided data on the Human Development Index in Brazil. Deaths by misclassified or unspecified causes (garbage codes) were redistributed proportionally to known causes. Age-standardized mortality rates used the world population as reference. Prais-Winsten autoregression allowed calculating trends for each region, sex and cancer type. RESULTS: Trends were predominantly on the increase in the North and Northeast, whereas they were mainly decreasing or stationary in the South, Southeast, and Center-West. Also, the variation of trends within intermediate regions was more pronounced in the North and Northeast. Intermediate regions with higher human development, government health spending, and hospital beds had more favorable trends for all cancers and many specific cancer types. CONCLUSIONS: Patterns of cancer trends in the country reflect differences in human development and the provision of health resources across the regions. Increasing trends of cancer mortality in low-income Brazilian regions can overburden their already fragile health infrastructure. Improving the healthcare provision and reducing socioeconomic disparities can prevent increasing trends of mortality by all cancers and specific cancer types in Brazilian more impoverished regions.

Health geography and the 'performative' turn: making space for the audio-visual in ethnographic health research.

The purpose of this paper is to critically reflect on the added value of video in ethnographic research that seeks to understand peoples' lived experiences of health and place. Of particular interest is the potential for video to elicit the embodied, multisensory and relational nature of people's place experiences that are the focus of much recent health geography research. We draw on our experiences of using video in an ethnographic study that sought to explore the experiences of people with intellectual disabilities engaged in nature based (or 'green care') therapeutic interventions for health and wellbeing. We argue that video has the potential to capture aspects of people's wellbeing experiences that may be lost using other methods, such as observational field noting. Consideration is also given to how researchers using video methods should seek to (re)present people's wellbeing experiences, as well as the practical and ethical challenges that this approach has for those working in the field of health geography.

Geographic analysis and estimation of hepatitis C cases in migrant populations living in Spain: is a country-based screening strategy appropriate?

Background: Spain needs to increase the number of new known cases in order to achieve the goal of eliminating hepatitis C virus (HCV) by 2030. The aim of this study was to estimate the number of HCV cases among the migrant population in Spain and propose different scenarios for micro-elimination strategies, targeting the most relevant migrant groups. Methodology: this epidemiological and demographic cross-sectional descriptive study employed a systematic approach to estimate the number of migrants infected by HCV in Spain. Estimates are based on demographic data and details the size of the foreign-born population living in every Spanish province and the anti-HVC+ prevalence rates in their respective countries of origin. Results: in Spain, there are 100,268 estimated cases of anti-HCV+ among the total adult migrant population who live in the country. The estimated cases of anti-HCV+ among migrants from moderate-high endemic countries with a prevalence of ≥ 2%, > 3%, > 4% and > 5% are 48,979, 48,029, 24,176 and 15,646, respectively. The anti-HCV+ endemic countries (≥ 2%) that contribute to the highest number of estimated cases in Spain are Romania, Italy, Pakistan, Ukraine, Senegal, Russia and Nigeria. The autonomous communities with the highest prevalence and number of estimated anti-HCV+ cases among migrant population are Catalonia, Valencian Community, Madrid and Andalusia, respectively. Conclusion: these data show the need to establish HCV screening strategies for the migrant population in Spain and, particularly, in the most affected areas. The strategy should target those migrant communities with a higher prevalence and a higher number of estimated cases, such as people from Eastern Europe, Sub-Saharan Africa and Pakistan

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Geostatistical predictive modeling for asthma and chronic obstructive pulmonary disease using socioeconomic and environmental determinants.

The spatial distribution of the prevalence of asthma and chronic obstructive pulmonary disease (COPD) remains under the influence of a wide array of environmental, climatic, and socioeconomic determinants. However, a large proportion of these influences remain unexplained. In completion, this study examined the spatial associations between asthma/COPD morbidity and their determinants using ordinary least squares (OLS) and geographically weighted regressions (GWR). Inpatient records collected from the secondary and tertiary care hospitals in Kandy from 2010 to 2014 were considered as the dependent variable. Potential risk factors (explanatory variables) were identified in four distinguished classes: 1) meteorological factors, (2) direct and indirect factors of air pollution, (3) socioeconomic factors, and (4) characteristics of the physical environment. All possible combinations of candidate explanatory variables were evaluated through an exploratory regression. A comparison between the regression models was also explored. The best OLS regression models revealed about 55% of asthma variation and 62% of COPD variation while GWR models yielded 78% and 74% of the variation of asthma and COPD occurrences respectively. Relative humidity, proximity to roads (0-200 m), road density, use of firewood as a source of fuel, and elevation play a vital role in predicting morbidity from asthma and COPD. Both local and global regression models are important in assessing spatial relationships of asthma and COPD. However, the local models exhibit a better prediction capability for assessing non-stationary relationships of asthma and COPD than global models. The geostatistical aspects used in this study may also provide insights for evaluating heterogeneous environmental risk factors in other epidemiological studies across different spatial settings.

Blind Spots: Spatial analytics can identify nonrandom geographic variation in first episode psychosis program enrollments.

AIM: To apply spatial analytics to an underway first episode psychosis program to identify areas of significant variation in the geographical distribution of program enrollees from an underlying at-risk population. METHODS: Adaptive bandwidth kernel smoothing was used to estimate spatial density functions from program enrollee home addresses and a control population computed from US Census data. A relative risk surface derived from the ratio of these functions was used to discover under-represented areas, or areas from which fewer enrollees where produced than suggested by the underlying population density at the P < .05 level of statistical significance. As a test application of this analysis, a comprehensive list of primary care providers in the program catchment was extracted from the National Plan and Provider Enumeration System and spatially compared to the under-represented areas. RESULTS: This approach identified under-represented areas containing 27.5% of the total program catchment area and 16% of the control population, yet had yielded zero program participants. These under-represented areas contained 179 primary care providers of the 2,337 in the total catchment area. CONCLUSIONS: Findings of nonrandom spatial variation in program enrollment is valuable data for those evaluating the impact of and implementing improvements for recruitment to specialty clinics serving geographically-defined catchments. Positive findings from this preliminary study warrant further development of the predictive model as well as measurement of the impact on enrollment from recruitment interventions driven by these findings.

Geographic variation in sexual behavior can explain geospatial heterogeneity in the severity of the HIV epidemic in Malawi.

BACKGROUND: In sub-Saharan Africa, where ~ 25 million individuals are infected with HIV and transmission is predominantly heterosexual, there is substantial geographic variation in the severity of epidemics. This variation has yet to be explained. Here, we propose that it is due to geographic variation in the size of the high-risk group (HRG): the group with a high number of sex partners. We test our hypothesis by conducting a geospatial analysis of data from Malawi, where ~ 13% of women and ~ 8% of men are infected with HIV. METHODS: We used georeferenced HIV testing and behavioral data from ~ 14,000 participants of a nationally representative population-level survey: the 2010 Malawi Demographic and Health Survey (MDHS). We constructed gender-stratified epidemic surface prevalence (ESP) maps by spatially smoothing and interpolating the HIV testing data. We used the behavioral data to construct gender-stratified risk maps that reveal geographic variation in the size of the HRG. We tested our hypothesis by fitting gender-stratified spatial error regression (SER) models to the MDHS data. RESULTS: The ESP maps show considerable geographic variation in prevalence: 1-29% (women), 1-20% (men). Risk maps reveal substantial geographic variation in the size of the HRG: 0-40% (women), 16-58% (men). Prevalence and the size of the HRG are highest in urban centers. However, the majority of HIV-infected individuals (~75% of women, ~ 80% of men) live in rural areas, as does most of the HRG (~ 80% of women, ~ 85% of men). We identify a significant (P < 0.001) geospatial relationship linking the size of the HRG with prevalence: the greater the size, the higher the prevalence. SER models show HIV prevalence in women is expected to exceed the national average in districts where > 20% of women are in the HRG. Most importantly, the SER models show that geographic variation in the size of the HRG can explain a substantial proportion (73% for women, 67% for men) of the geographic variation in epidemic severity. CONCLUSIONS: Taken together, our results provide substantial support for our hypothesis. They provide a potential mechanistic explanation for the geographic variation in the severity of the HIV epidemic in Malawi and, potentially, in other countries in sub-Saharan Africa.

ß-Thalassemia Mutations in Jamaica: Geographic Variation in Small Communities.

Over the last 43 years, surveys of over 200,000 subjects in Jamaica have identified ß-thalassemia (ß-thal) mutations. In most, these genes were detected at birth in patients with sickle cell-ß-thal and so the prevalence and distribution would not be influenced by subsequent clinical course. There were two newborn populations, 100,000 deliveries in the corporate area between 1973-1981 and 84,940 in south and western Jamaica between 2008-2016. A third population, which derived from the Manchester Project in central Jamaica, screened 16,612 secondary school children, aged predominantly 15-19 years, and identified 150 students with the ß-thal trait and 11 with sickle cell [Hb S (HBB: c.20A>T)]- or Hb C (HBB: c.19G>A)-ß-thal. The latter patients may have been subject to symptomatic selection, but this should not have affected those with ß-thal trait. Of the 24 different molecular mutations, ß0-thal genes accounted for 10.0-27.0% of these groups and most common was IVS-II-849 (A>G) (HBB: c.316-2A>G). Of the ß+ mutations, seven subjects had severe genes with low levels of ß chain synthesis but the majority were benign mutations in the promoter region. The -29 (A>G) (HBB: c.-79A>G) mutation dominated in the newborn study in Kingston, similar to experiences in Guadeloupe and African Americans but the -88 (C>T) (HBB: c.-138C>T) mutation was more common among school students in central Jamaica. Caribbean populations are genetically heterogeneous but variations within different parts of Jamaica is of potential importance for prenatal diagnosis and genetic counseling. This information may also be useful among the large Jamaican diaspora.

Evaluation of data accuracies within a comprehensive geospatial-health data surveillance platform: SOMAARTH Demographic Development and Environmental Surveillance Site, Palwal, Haryana, India.

Evidence exists of an increasing prevalence of chronic conditions within developed and developing nations, notably for priority population groups. The need for the collection of geospatial data to monitor the health impact of rapid social-environmental and economic changes occurring in these countries is being increasingly recognized. Rigorous accuracy assessment of such geospatial data is required to enable error estimation, and ultimately, data utility for exploring population health. This research outlines findings from a field-based evaluation exercise of the SOMAARTH DDESS geospatial-health platform. Participatory-based mixed methods have been employed within Palwal-India to capture villager perspectives on built infrastructure across 51 villages. This study, conducted in 2013, included an assessment of data element position and attribute accuracy undertaken in six villages, documenting mapping errors and land parcel changes. Descriptive analyses of 5.1% (n = 455) of land parcels highlighted some discrepancies in position (6.4%) and attribute (4.2%) accuracy, and land parcel changes (17.4%). Furthermore, the evaluation led to a refinement of the existing geospatial health platform incorporating ground-truthed reflections from the participatory field exercise. The evaluation of geospatial data accuracies contributes to understandings on global public health surveillance systems, outlining the need to systematically consider assessment of environmental features in relation to lifestyle-related diseases.

Analysis of Cancer Deaths at the County Level Pinpoints Hot Spots for Action.

Such localized information can help improve resource allocation.

Spatiotemporal mapping of cervical cancer incidence highlights need for targeted prevention in Songkhla province, Thailand.

BACKGROUND: The national cervical cancer screening program in Thailand has been successful in reducing overall burden from this disease. However, evaluation on spatial and temporal scales is needed to assess the efficacy of this program in smaller regions. Here, we geographically assess incidence in a province with a uniquely heterogeneous distribution of lifestyle factors associated with religiosity. METHODS: Cervical cancer cases were extracted from the provincial cancer registry from 1989 to 2013. Age-adjusted incidence rates were calculated using population statistics from the census bureau and adjusted to the Segi world standard population. Bayesian hierarchical modelling was employed to spatiotemporally map cervical cancer incidence trends in Songkhla province in 5-year period. RESULTS: Overall, the incidence of cervical cancer decreased in Songkhla province. The three districts with a Muslim population of greater than 70% had consistently lower cervical cancer rates from 1989 to 2013 compared with the rest of the predominantly Buddhist districts. Hotspots of incidence were identified in Sadao, Hat Yai and the juncture of Mueang Songkhla and Singhanakhon in each 5-year period. CONCLUSIONS: Distinct cervical cancer incidence trends by religion over time indicate differences in sexual habits, lifestyle and religion-associated culture between Muslims and Buddhists, and suggest divergent risk factor profiles for these groups. The high incidence rates in Sadao and Hat Yai is likely explained by the main road to Malaysia, which runs across these two areas and has frequent commercial sex trade. Female sex workers should be targeted as a vulnerable population for screening efforts to address this continuing burden of cervical cancer.

Illuminating the lifecourse of place in the longitudinal study of neighbourhoods and health.

Place and health are inextricably entwined. Whilst insights have been gained into the associations between places, such as neighbourhoods, and health, the understanding of these relationships remains only partial. One of the reasons for this relates to time and change and the inter-relationships between the dynamic nature of both neighbourhoods and health. This paper argues that the lifecourse of place can be used as a conceptual framework to understand the evolution and ongoing development of neighbourhoods, and their impact on the geographies of health, past, present and future. Moreover, this paper discusses the capacity of a longitudinal form of enquiry - latent transition analysis - that is able to operationalise conceptual models of the lifecourse of place. To date, latent transition analysis has not been applied to the study of neighbourhoods and health. Drawing on research across a range of disciplines including developmental psychology, sociology, geography and epidemiology, this paper also considers praxis-based implications and recommendations for applications of latent transition analysis that aim to advance understanding of how neighbourhoods affect health in and over time.

The benefits of utilising geo-mapping for visualising the vitamin D status of Dublin city and the surrounding urban districts.

CONTEXT: There have been few published reports of visualising vitamin D status at a micro level, i.e., within large individual urban centres of countries. OBJECTIVE: To produce a visual map of the vitamin D status [25-hydroxy vitamin D-25(OH)D] of a large urban centre (n > 350,000) incorporating the regions of Dublin city that constitute the general practitioner catchment area of a large academic teaching adult hospital. DESIGN, SETTING AND PARTICIPANTS: An observational investigation of 5287 free living Irish adults (>18 years). RESULTS: Approximately, 15.2 % of those sampled in the winter period (October-February) were vitamin D deficient (<30 nmol/L) compared with 10.8 % of those sampled in the summer period (March-September). Vitamin D tests requested from the most social economically deprived urban locations (Dublin 8 and Lucan postal districts) had the highest rates of deficiency (23.5 and 20.4 %, respectively, both seasons). On average, females had a significantly higher 25(OH)D concentration compared with males (57.9 vs 52.3 nmol/L, respectively), while the younger participants (18-50 years) mean 25(OH)D concentration was 27 % lower in winter and 20.7 % lower in summer in comparison with the older participants (>50 years) (P < 0.0001). CONCLUSIONS: For the first time in Ireland, a visual depiction of data can be used to aid in the rapid identification of vitamin D status trends within a major urban area. These findings provide useful data to help inform public health policy regarding endemic vitamin D insufficiency to help target the population groups and resident location areas most at risk.

Geografía de la atención sanitaria para la CMA en el Área III-IV de la Comunidad de Cantabria, España / Geograpy of health care for day surgery in the III-IV área of the community of Cantabria-Spain

Justificación: se evalúa la distribución y relación de la patología de la CMA (Cirugía Mayor Ambulatoria), y los centros de salud aplicando la geografía de la atención sanitaria. Se analizan 6.296 pacientes intervenidos por CMA, (3290 en 2013; 3.006 en 2014) incluidos en el hospital Sierrallana y Tres Mares, área III y IV de la Comunidad de Cantabria-España Se aplicó la codificación en GRDs y clasificación internacional de enfermedades, CIE-9. Hay 307 poblaciones donde se ha realizado CMA en 2013, y 306 en 2014. Se añaden 2 poblaciones más Aguilar de Campoo y Cillorigo, en 2014. Aumentan en Valderedible y Matamorosa, y disminuye en Unquera. En las poblaciones con mayores ASA I y ASA II, disminuyen los ASA III y ASA IV en 2014, con respecto a 2013. De igual manera la población de Torrelavega, que es la principal del área III-IV, tiene el mayor número de ASA IV. Se observa que en 2013 en las poblaciones cercanas se hicieron más ASAs moderados II y III que en 2014. En población grandes, los pacientes con ASA II y III aumentan y son subsidiarios de ser atendidos como CMA. En la geografía de la salud del procedimiento, se observa que la población con más habitantes del área III-IV, (Torrelavega), presenta mayor cantidad de procedimientos de CMA, en este caso la catarata cortical. Se mantiene la relación entre número de habitantes y CMA por población, lo que ayuda a estimar cálculo de coste y dotación. Justificación: se evalúa la distribución y relación de la patología de la CMA (Cirugía Mayor Ambulatoria), y los centros de salud aplicando la geografía de la atención sanitaria. Se analizan 6.296 pacientes intervenidos por CMA, (3290 en 2013; 3.006 en 2014) incluidos en el hospital Sierrallana y Tres Mares, área III y IV de la Comunidad de Cantabria-España Se aplicó la codificación en GRDs y clasificación internacional de enfermedades, CIE-9. Hay 307 poblaciones donde se ha realizado CMA en 2013, y 306 en 2014. Se añaden 2 poblaciones más Aguilar de Campoo y Cillorigo, en 2014. Aumentan en Valderedible y Matamorosa, y disminuye en Unquera. En las poblaciones con mayores ASA I y ASA II, disminuyen los ASA III y ASA IV en 2014, con respecto a 2013. De igual manera la población de Torrelavega, que es la principal del área III-IV, tiene el mayor número de ASA IV. Se observa que en 2013 en las poblaciones cercanas se hicieron más ASAs moderados II y III que en 2014. En población grandes, los pacientes con ASA II y III aumentan y son subsidiarios de ser atendidos como CMA. En la geografía de la salud del procedimiento, se observa que la población con más habitantes del área III-IV, (Torrelavega), presenta mayor cantidad de procedimientos de CMA, en este caso la catarata cortical. Se mantiene la relación entre número de habitantes y CMA por población, lo que ayuda a estimar cálculo de coste y dotación

Justification: The aim from the point of view of geography evaluate health care as distributed and pathology which deals with the Day Surgery (DSU) relates, and health centers. 6,296 patients operated by DSU are analyzed (3290 in 2013; 3,006 in 2014) included in the hospital Sierrallana and Tres Mares, area III and IV of the Community of Cantabria-Spain coding international classification was applied in DRGs and disease, ICD-9. There are 307 locations where there has been DSU in 2013 and 306 in 2014. 2 populations most Aguilar de Campo and Cillorigo in 2014. Increases in Valderedible and Matamorosa, and decreases in Unquera are added. In populations with higher ASA I and ASA II, decrease ASA III and IV in 2014, compared to 2013. Similarly, the population of Torrelavega, which is the main area III-IV, has the largest number of ASA IV. It is noted that more moderate ASAs II and III in 2014 were made in 2013 in the nearby towns. American Society of Anesthesiologists (ASA). In large population, patients with ASA II and III increase and are subsidiary to be served as DSU. In the geography of the health of the procedure, it is observed that the population most populous area III-IV, (Torrelavega) presents as many procedures DSU, in this case the cortical cataract. The relationship between number of inhabitants and population is maintained by DSU, which helps estimate cost calculation and allocation

Geo-spatial Informatics in International Public Health Nursing Education.

This poster describes results of an undergraduate nursing informatics experience. Students applied geo-spatial methods to community assessments in two urban regions of New Zealand and the United States. Students used the Omaha System standardized language to code their observations during a brief community assessment activity and entered their data into a mapping program developed in Esri ArcGIS Online, a geographic information system. Results will be displayed in tables and maps to allow comparison among the communities. The next generation of nurses can employ geo-spatial informatics methods to contribute to innovative community assessment, planning and policy development.

On the road to personalised and precision geomedicine: medical geology and a renewed call for interdisciplinarity.

Our health depends on where we currently live, as well as on where we have lived in the past and for how long in each place. An individual's place history is particularly relevant in conditions with long latency between exposures and clinical manifestations, as is the case in many types of cancer and chronic conditions. A patient's geographic history should routinely be considered by physicians when diagnosing and treating individual patients. It can provide useful contextual environmental information (and the corresponding health risks) about the patient, and should thus form an essential part of every electronic patient/health record. Medical geology investigations, in their attempt to document the complex relationships between the environment and human health, typically involve a multitude of disciplines and expertise. Arguably, the spatial component is the one factor that ties in all these disciplines together in medical geology studies. In a general sense, epidemiology, statistical genetics, geoscience, geomedical engineering and public and environmental health informatics tend to study data in terms of populations, whereas medicine (including personalised and precision geomedicine, and lifestyle medicine), genetics, genomics, toxicology and biomedical/health informatics more likely work on individuals or some individual mechanism describing disease. This article introduces with examples the core concepts of medical geology and geomedicine. The ultimate goals of prediction, prevention and personalised treatment in the case of geology-dependent disease can only be realised through an intensive multiple-disciplinary approach, where the various relevant disciplines collaborate together and complement each other in additive (multidisciplinary), interactive (interdisciplinary) and holistic (transdisciplinary and cross-disciplinary) manners.

Efficient estimation and prediction for the Bayesian binary spatial model with flexible link functions.

Spatial generalized linear mixed models (SGLMMs) are popular models for spatial data with a non-Gaussian response. Binomial SGLMMs with logit or probit link functions are often used to model spatially dependent binomial random variables. It is known that for independent binomial data, the robit regression model provides a more robust (against extreme observations) alternative to the more popular logistic and probit models. In this article, we introduce a Bayesian spatial robit model for spatially dependent binomial data. Since constructing a meaningful prior on the link function parameter as well as the spatial correlation parameters in SGLMMs is difficult, we propose an empirical Bayes (EB) approach for the estimation of these parameters as well as for the prediction of the random effects. The EB methodology is implemented by efficient importance sampling methods based on Markov chain Monte Carlo (MCMC) algorithms. Our simulation study shows that the robit model is robust against model misspecification, and our EB method results in estimates with less bias than full Bayesian (FB) analysis. The methodology is applied to a Celastrus Orbiculatus data, and a Rhizoctonia root data. For the former, which is known to contain outlying observations, the robit model is shown to do better for predicting the spatial distribution of an invasive species. For the latter, our approach is doing as well as the classical models for predicting the disease severity for a root disease, as the probit link is shown to be appropriate. Though this article is written for Binomial SGLMMs for brevity, the EB methodology is more general and can be applied to other types of SGLMMs. In the accompanying R package geoBayes, implementations for other SGLMMs such as Poisson and Gamma SGLMMs are provided.