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Background: There is growing concern of how climate change could affect public health, due to the increase number of extreme climate events. Hence, the study of the role that climate events play on the distribution of waterborne diseases, like Hepatitis A, could be key for developing new prevention approaches., Objective: To investigate the association between climate factors and Hepatitis A in Spain between 2010 and 2014., Methods: Weekly Hepatitis A cases between 2010 and 2014 were obtained from the Spanish Epidemiology Surveillance Network. Climate variables (weekly cumulative rainfall, rainy days, storm days and snow days) were obtained from National Climatic Data Center (NOAA satellite and information Service of USA). Each municipality was assigned to the nearest weather station (N=73). A Mixed-Effects Poisson regression was performed to estimate Incidence Rate Ratios (IRR), including a time lag of 2, 3 and 4weeks (most probable incubation period for Hepatitis A)., Results: Rainfall higher than 90th percentile (extreme precipitation) was associated with increased number of Hepatitis A cases 2weeks (IRR=1.24 CI 95%=1.09-1.40) and 4weeks after the event (IRR=1.15 CI 95%=1.01-1.30). An extra rainy day increased the risk of Hepatitis A two weeks after (IRR=1.03 CI 95%=1.01-1.05). We found higher risk of Hepatitis A two weeks after each extra storm day (IRR=1.06 CI 95%=1.00-1.12), and lower risk with 3 and 4weeks' lag (IRR=0.93 CI 95%=0.88-0.99 for lag3; IRR=0.94 CI 95%=0.88-0.99 for lag 4)., Conclusions: There is an increased risk of Hepatitis A 2weeks after water-related climate events. Including meteorological information in surveillance systems might improve to develop early prevention strategies for waterborne diseases., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: The transmission of malaria is intense in the majority of the countries of sub-Saharan Africa, particularly in those that are located along the Equatorial strip. The present study aimed to describe the current distribution of malaria prevalence among children and its environment-related factors as well as to detect malaria spatial clusters in the district of Bata, in Equatorial Guinea., Methods: From June to August 2013 a representative cross-sectional survey using a multistage, stratified, cluster-selected sample was carried out of children in urban and rural areas of Bata District. All children were tested for malaria using rapid diagnostic tests (RDTs). Results were linked to each household by global position system data. Two cluster analysis methods were used: hot spot analysis using the Getis-Ord Gi statistic, and the SaTScan™ spatial statistic estimates, based on the assumption of a Poisson distribution to detect spatial clusters. In addition, univariate associations and Poisson regression model were used to explore the association between malaria prevalence at household level with different environmental factors., Results: A total of 1416 children aged 2 months to 15 years living in 417 households were included in this study. Malaria prevalence by RDTs was 47.53%, being highest in the age group 6-15 years (63.24%, p < 0.001). Those children living in rural areas were there malaria risk is greater (65.81%) (p < 0.001). Malaria prevalence was higher in those houses located <1 km from a river and <3 km to a forest (IRR: 1.31; 95% CI 1.13-1.51 and IRR: 1.44; 95% CI 1.25-1.66, respectively). Poisson regression analysis also showed a decrease in malaria prevalence with altitude (IRR: 0.73; 95% CI 0.62-0.86). A significant cluster inland of the district, in rural areas has been found., Conclusions: This study reveals a high prevalence of RDT-based malaria among children in Bata district. Those households situated in inland rural areas, near to a river, a green area and/or at low altitude were a risk factor for malaria. Spatial tools can help policy makers to promote new recommendations for malaria control.

Background: Central nervous system tumors (CNS) are the most frequent solid tumor in children. Causes of CNS tumors are mainly unknown and only 5% of the cases can be explained by genetic predisposition. We studied the effects of environmental exposure on the incidence of CNS tumors in children by subtype, according to exposure to industrial and/or urban environment, exposure to crops and according to socio-economic status of the child., Methods: We carried out a population-based case-control study of CNS tumors in Spain, covering 714 incident cases collected from the Spanish Registry of Childhood Tumors (period 1996-2011) and 4284 controls, individually matched by year of birth, sex, and autonomous region of residence. We built a covariate to approximate the exposure to industrial and/or urban environment and a covariate for the exposure to crops (GCI) using the coordinates of the home addresses of the children. We used the 2001 Census to obtain information about socio-economic status (SES). We fitted logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs)., Results: The results for all CNS tumors showed an excess risk (OR = 1.37; 95%CI = 1.09-1.73) for SES, i.e., children living in the least deprived areas had 37% more risk of CNS tumor than children living in the most deprived areas. For GCI, an increase of 10% in crop surface in the 1-km buffer around the residence implied an increase of 22% in the OR (OR = 1.22; 95%CI = 1.15-1.29). Children living in the intersection of industrial and urban areas could have a greater risk of CNS tumors than children who live outside these areas (OR = 1.20; 95%CI = 0.82-1.77). Living in urban areas (OR = 0.90; 95%CI = 0.65-1.24) or industrial areas (OR = 0.96; 95%CI = 0.81-1.77) did not seem to increase the risk for all CNS tumors together. By subtype, Astrocytomas, Intracranial and intraspinal embryonal tumors, and other gliomas showed similar results., Conclusion: Our results suggest that higher socioeconomic status and exposure to crops could increase the risk of CNS tumors in children.

Few epidemiologic studies have explored risk factors for bone tumors in children, and the role of environmental factors needs to be analyzed. Our objective was to ascertain the association between residential proximity to industrial plants and urban areas and risk of bone tumors in children, taking into account industrial groups and toxic pollutants released. A population-based case-control study of childhood bone cancer in Spain was carried out, covering 114 incident cases obtained from the Spanish Registry of Childhood Tumors (between 1996 and 2011), and 684 controls individually matched by sex, year of birth, and autonomous region of residence. Distances from the subject's residences to the 1271 industries and the 30 urban areas (towns) with ≥75,000 inhabitants located in the study area were computed. Unconditional logistic regression models were fitted to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance (from 1km to 3km) to industrial and urban areas, with adjustment for matching variables and sociodemographic indicators. Excess risk (OR; 95%CI) of bone tumors in children was detected for children close to industrial facilities as a whole (2.33; 1.17-4.63 at 3km) - particularly surface treatment of metals (OR=2.50; 95%CI=1.13-5.56 at 2km), production and processing of metals (OR=3.30; 95%CI=1.41-7.77 at 2.5km), urban waste-water treatment plants (OR=4.41; 95%CI=1.62-11.98 at 2km), hazardous waste (OR=4.63; 95%CI=1.37-15.61 at 2km), disposal or recycling of animal waste (OR=4.73; 95%CI=1.40-15.97 at 2km), cement and lime (OR=3.89; 95%CI=1.19-12.77 at 2.5km), and combustion installations (OR=3.85; 95%CI=1.39-10.66 at 3km)-, and urban areas (4.43; 1.80-10.92). These findings support the need for more detailed exposure assessment of certain toxics released by these facilities., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Background: Few epidemiologic studies have explored risk factors for rare tumors in children, and the role of environmental factors needs to be assessed., Objectives: To ascertain the effect of residential proximity to both industrial and urban areas on childhood cancer risk, taking industrial groups into account., Methods: We conducted a population-based case-control study of five childhood cancers in Spain (retinoblastoma, hepatic tumors, soft tissue sarcomas, germ cell tumors, and other epithelial neoplasms/melanomas), including 557 incident cases from the Spanish Registry of Childhood Tumors (period 1996-2011), and 3342 controls individually matched by year of birth, sex, and region of residence. Distances were computed from the residences to the 1271 industries and the 30 urban areas with ≥75,000 inhabitants located in the study area. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance to industrial and urban pollution sources were calculated, with adjustment for matching variables and socioeconomic confounders., Results: Children living near industrial and urban areas as a whole showed no excess risk for any of the tumors analyzed. However, isolated statistical associations (OR; 95%CI) were found between retinoblastoma and proximity to industries involved in glass and mineral fibers (2.49; 1.01-6.12 at 3km) and organic chemical industries (2.54; 1.10-5.90 at 2km). Moreover, soft tissue sarcomas registered the lower risks in the environs of industries as a whole (0.59; 0.38-0.93 at 4km)., Conclusions: We have found isolated statistical associations between retinoblastoma and proximity to industries involved in glass and mineral fibers and organic chemical industries., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Neuroblastoma is the most common extracranial solid tumor in children but its etiology is not clearly understood. While a small fraction of cases might be attributable to genetic factors, the role of environmental pollution factors needs to be assessed., Objectives: To ascertain the effect of residential proximity to both industrial and urban areas on neuroblastoma risk, taking into account industrial groups and toxic substances released., Methods: We conducted a population-based case-control study of neuroblastoma in Spain, including 398 incident cases gathered from the Spanish Registry of Childhood Tumors (period 1996-2011), and 2388 controls individually matched by year of birth, sex, and region of residence. Distances were computed from the respective subject's residences to the 1271 industries and the 30 urban areas with ≥75,000 inhabitants located in the study area. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance (from 1km to 5km) to industrial and urban pollution sources were calculated, with adjustment for matching variables and socioeconomic confounders., Results: Excess risk (OR; 95%CI) of neuroblastoma was detected for the intersection between industrial and urban areas: (2.52; 1.20-5.30) for industrial distance of 1km, and (1.99; 1.17-3.37) for industrial distance of 2km. By industrial groups, excess risks were observed near 'Production of metals' (OR=2.05; 95%CI=1.16-3.64 at 1.5km), 'Surface treatment of metals' (OR=1.89; 95%CI=1.10-3.28 at 1km), 'Mines' (OR=5.82; 95%CI=1.04-32.43 at 1.5km), 'Explosives/pyrotechnics' (OR=4.04; 95%CI=1.31-12.42 at 4km), and 'Urban waste-water treatment plants' (OR=2.14; 95%CI=1.08-4.27 at 1.5km)., Conclusions: These findings support the need for more detailed exposure assessment of certain substances released by these industries., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: Childhood cancer is the main cause of disease-related death in children in Spain. Although little is known about the etiology, environmental factors are potential explanations for a fraction of the cases. Previous studies have shown pesticides to be associated with childhood cancer. The difficulty of collecting personal environmental exposure data is an important limitation; this lack of information about pesticides motivates the development of new methods to subrogate this exposure. We developed a crop exposure index based on geographic information to study the relationship between exposure to different types of crops and risk of childhood tumors., Methods: We conducted a population-based case-control study of childhood cancer covering 3350 cases and 20,365 controls in two Spanish regions. We used CORINE Land Cover to obtain data about agricultural land use. We created a 1 km buffer around every child and calculated the percentage of crop surface within the buffer (Global Crop Index) for total crops and for individual types of crops. We fitted mixed multiple unconditional logistic regression models by diagnostic group., Results: We found excess of risk among children living in the proximity of crops. For total crops our results showed excesses of risk for almost all diagnostic groups and increasing risk with increasing crop index value. Analyses by region and individual type of crop also showed excess of risk., Conclusion: The results suggest that living in the proximity of cultivated land could be a risk factor for several types of cancer in children.

Background: Few risk factors for childhood renal tumors are well established. While a small fraction of cases might be attributable to susceptibility genes and congenital anomalies, the role of environmental factors needs to be assessed., Objectives: To explore the possible association between residential proximity to environmental pollution sources (industrial and urban areas, and agricultural crops) and childhood renal cancer, taking into account industrial groups and toxic substances released., Methods: We conducted a population-based case-control study of childhood renal cancer in Spain, including 213 incident cases gathered from the Spanish Registry of Childhood Tumors (period 1996-2011), and 1278 controls individually matched by year of birth, sex, and region of residence. Distances were computed from the respective subject's residences to the 1271 industries, the 30 urban areas with ≥75,000 inhabitants, and the agricultural crops located in the study area. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance to pollution sources were calculated, with adjustment for matching variables and socioeconomic confounders., Results: Excess risk (OR; 95%CI) of childhood renal tumors was observed for children living near (≤2.5km) industrial installations as a whole (1.97; 1.13-3.42) - particularly glass and mineral fibers (2.69; 1.19-6.08), galvanization (2.66; 1.14-6.22), hazardous waste (2.59; 1.25-5.37), ceramic (2.35; 1.06-5.21), surface treatment of metals (2.25; 1.24-4.08), organic chemical industry (2.22; 1.15-4.26), food and beverage sector (2.19; 1.18-4.07), urban and waste-water treatment plants (2.14; 1.07-4.30), and production and processing of metals (1.98; 1.03-3.82) -, and in the proximity of agricultural crops (3.16; 1.54-8.89 for children with percentage of crop surface ≥24.35% in a 1-km buffer around their residences)., Conclusions: Our study provides some epidemiological evidence that living near certain industrial areas and agricultural crops may be a risk factor for childhood renal cancer., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objective: To estimate the areas of greatest density of road traffic accidents with fatalities at 24 hours per km(2)/year in Spain from 2008 to 2011, using a geographic information system., Methods: Accidents were geocodified using the road and kilometer points where they occurred. The average nearest neighbor was calculated to detect possible clusters and to obtain the bandwidth for kernel density estimation., Results: A total of 4775 accidents were analyzed, of which 73.3% occurred on conventional roads. The estimated average distance between accidents was 1,242 meters, and the average expected distance was 10,738 meters. The nearest neighbor index was 0.11, indicating that there were aggregations of accidents in space. A map showing the kernel density was obtained with a resolution of 1 km(2), which identified the areas of highest density., Conclusions: This methodology allowed a better approximation to locating accident risks by taking into account kilometer points. The map shows areas where there was a greater density of accidents. This could be an advantage in decision-making by the relevant authorities., (Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.)

Background: Few risk factors for the childhood leukemia are well established. While a small fraction of cases of childhood leukemia might be partially attributable to some diseases or ionizing radiation exposure, the role of industrial and urban pollution also needs to be assessed., Objectives: To ascertain the possible effect of residential proximity to both industrial and urban areas on childhood leukemia, taking into account industrial groups and toxic substances released., Methods: We conducted a population-based case-control study of childhood leukemia in Spain, covering 638 incident cases gathered from the Spanish Registry of Childhood Tumors and for those Autonomous Regions with 100% coverage (period 1990-2011), and 13,188 controls, individually matched by year of birth, sex, and autonomous region of residence. Distances were computed from the respective subject's residences to the 1068 industries and the 157 urban areas with ≥10,000 inhabitants, located in the study area. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance to industrial and urban pollution sources were calculated, with adjustment for matching variables., Results: Excess risk of childhood leukemia was observed for children living near (≤2.5 km) industries (OR=1.31; 95%CI=1.03-1.67) - particularly glass and mineral fibers (OR=2.42; 95%CI=1.49-3.92), surface treatment using organic solvents (OR=1.87; 95%CI=1.24-2.83), galvanization (OR=1.86; 95%CI=1.07-3.21), production and processing of metals (OR=1.69; 95%CI=1.22-2.34), and surface treatment of metals (OR=1.62; 95%CI=1.22-2.15) - , and urban areas (OR=1.36; 95%CI=1.02-1.80)., Conclusions: Our study furnishes some evidence that living in the proximity of industrial and urban sites may be a risk factor for childhood leukemia., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objective: An excess of mortality was detected in Spain in February and March 2012 by the Spanish daily mortality surveillance system and the «European monitoring of excess mortality for public health action» program. The objective of this article was to determine whether this excess could be attributed to influenza in this period., Methods: Excess mortality from all causes from 2006 to 2012 were studied using time series in the Spanish daily mortality surveillance system, and Poisson regression in the European mortality surveillance system, as well as the FluMOMO model, which estimates the mortality attributable to influenza. Excess mortality due to influenza and pneumonia attributable to influenza were studied by a modification of the Serfling model. To detect the periods of excess, we compared observed and expected mortality., Results: In February and March 2012, both the Spanish daily mortality surveillance system and the European mortality surveillance system detected a mortality excess of 8,110 and 10,872 deaths (mortality ratio (MR): 1.22 (95% CI:1.21-1.23) and 1.32 (95% CI: 1.29-1.31), respectively). In the 2011-12 season, the FluMOMO model identified the maximum percentage (97%) of deaths attributable to influenza in people older than 64 years with respect to the mortality total associated with influenza (13,822 deaths). The rate of excess mortality due to influenza and pneumonia and respiratory causes in people older than 64 years, obtained by the Serfling model, also reached a peak in the 2011-2012 season: 18.07 and 77.20, deaths per 100,000 inhabitants, respectively., Conclusion: A significant increase in mortality in elderly people in Spain was detected by the Spanish daily mortality surveillance system and by the European mortality surveillance system in the winter of 2012, coinciding with a late influenza season, with a predominance of the A(H3N2) virus, and a cold wave in Spain. This study suggests that influenza could have been one of the main factors contributing to the mortality excess observed in the winter of 2012 in Spain., (Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.)

Background: Childhood cancer was the leading cause of death among children aged 1-14 years for 2012 in Spain. Leukemia has the highest incidence, followed by tumors of the central nervous system (CNS) and lymphomas (Hodgkin lymphoma, HL, and Non-Hodgkin's lymphoma, NHL). Spatial distribution of childhood cancer cases has been under concern with the aim of identifying potential risk factors., Objective: The two objectives are to study overall spatial clustering and cluster detection of cases of the three main childhood cancer causes, looking to increase etiological knowledge., Methods: We ran a case-control study. The cases were children aged 0 to 14 diagnosed with leukemia, lymphomas (HL and NHL) or CNS neoplasm in five Spanish regions for the period 1996-2011. As a control group, we used a sample from the Birth Registry matching every case by year of birth, autonomous region of residence and sex with six controls. We geocoded and validated the address of the cases and controls. For our two objectives we used two different methodologies. For the first, for overall spatial clustering detection, we used the differences of K functions from the spatial point patterns perspective proposed by Diggle and Chetwynd and the second, for cluster detection, we used the spatial scan statistic proposed by Kulldorff with a level for statistical significance of 0.05., Results: We had 1062 cases of leukemia, 714 cases of CNS, 92 of HL and 246 of NHL. Accordingly we had 6 times the number of controls, 6372 controls for leukemia, 4284 controls for CNS, 552 controls for HL and 1476 controls for NHL. We found variations in the estimated empirical D(s) for the different regions and cancers, including some overall spatial clustering for specific regions and distances. We did not find statistically significant clusters., Conclusions: The variations in the estimated empirical D(s) for the different regions and cancers could be partially explained by the differences in the spatial distribution of the population; however, according to the literature, we cannot discard environmental hazards or infections agents in the etiology of these cancers.

Background: Cardiovascular disease is the leading cause of death worldwide, but its spatial distribution is not homogeneous. The objective of this study is to analyze the spatial pattern of mortality from these diseases for men and women, in the populated urban area (AUP) of the municipality of Madrid, and to identify spatial aggregations., Methods: An ecological study was carried out by census tract, for men and women in 2010. Standardized Mortality Ratio (SMR), Relative Risk Smoothing (RRS) and Posterior Probability (PP) were calculated to consider the spatial pattern of the disease. To identify spatial clusters the Moran index (Moran I) and the Local Index of Spatial Autocorrelation (LISA) were used. The results were mapped., Results: SMR higher than 1.1 was observed mainly in central areas among men and in peripheral areas among women. The PP that RRS was higher than 1 surpassed 0.8 in the center and in the periphery, in both men and women. Moran's I was 0.04 for men and 0.03 for women (p <0.05 in both cases)., Conclusions: Sex differences were observed in the spatial distribution of mortality cases. RME RRS and PP maps showed a heterogeneous pattern in men, whereas in women a clearer pattern was detected, with a relatively higher risk in peripheral areas of the AUP. The LISA method showed similar patterns to those previously observed.

Cluster detection has become an important part of the agenda of epidemiologists and public health authorities, the identification of high- and low-risk areas is fundamental in the definition of public health strategies and in the suggestion of potential risks factors. Currently, there are different cluster detection techniques available, the most popular being those using windows to scan the areas within the studied region. However, when these areas are heterogeneous in populations' sizes, scan window methods can lead to inaccurate conclusions. In order to perform cluster detection over heterogeneously populated areas, we developed a method not based on scanning windows but instead on standard mortality ratios (SMR) using irregular spatial aggregation (ISA). Its extension, i.e. irregular spatial aggregation with covariates (ISAC), includes covariates with residuals from Poisson regression. We compared the performance of the method with the flexible shaped spatial scan statistic (FlexScan) using mortality data for stomach and bladder cancer for 8,098 Spanish towns. The results show a collection of clusters for stomach and bladder cancer similar to that detected by ISA and FlexScan. However, in general, clusters detected by FlexScan were bigger and include towns with SMR, which were not statistically significant. For bladder cancer, clusters detected by ISAC differed from those detected by ISA and FlexScan in shape and location. The ISA and ISAC methods could be an alternative to the traditional scan window methods for cluster detection over aggregated data when the areas under study are heterogeneous in terms of population. The simplicity and flexibility of the methods make them more attractive than methods based on more complicated algorithms.

Using mortality data from National Institute of Statistics in Spain, we analyzed trends of infectious disease mortality rates in Spain during 1980-2011 to provide information on surveillance and control of infectious diseases. During the study period, 628,673 infectious disease-related deaths occurred, the annual change in the mortality rate was -1.6%, and the average infectious disease mortality rate was 48.5 deaths/100,000 population. Although the beginning of HIV/AIDS epidemic led to an increased mortality rate, a decreased rate was observed by the end of the twentieth century. By codes from the International Classification of Diseases, 9th revision, the most frequent underlying cause of death was pneumonia. Emergence and reemergence of infectious diseases continue to be public health problems despite reduced mortality rates produced by various interventions. Therefore, surveillance and control systems should be reinforced with a goal of providing reliable data for useful decision making.

A retrospective, space-time study of whooping cough cases reported to the Public Health Agency of Barcelona, Spain between the years 2000 and 2011 is presented. It is based on 633 individual whooping cough cases and the 2006 population census from the Spanish National Statistics Institute, stratified by age and sex at the census tract level. Cluster identification was attempted using space-time scan statistic assuming a Poisson distribution and restricting temporal extent to 7 days and spatial distance to 500 m. Statistical calculations were performed with Stata 11 and SatScan and mapping was performed with ArcGis 10.0. Only clusters showing statistical significance (P <0.05) were mapped. The most likely cluster identified included five census tracts located in three neighbourhoods in central Barcelona during the week from 17 to 23 August 2011. This cluster included five cases compared with the expected level of 0.0021 (relative risk = 2436, P <0.001). In addition, 11 secondary significant space-time clusters were detected with secondary clusters occurring at different times and localizations. Spatial statistics is felt to be useful by complementing epidemiological surveillance systems through visualizing excess in the number of cases in space and time and thus increase the possibility of identifying outbreaks not reported by the surveillance system.

Objectives: To analyze the spatial pattern of legionellosis in Spain for men and women during the period 2003-2007 and to identify spatial clustering of risk., Methods: We identified the spatial pattern of the distribution of legionellosis rates based on calculation of rates by municipality through the direct method. Smoothing of these rates was performed by the Empirical Bayes method for studying the spatial pattern of disease for both sexes. We used Morańs index to analyze spatial autocorrelation rates globally. To calculate local rates, the Local Moran's Index [known as local indicators of spatial association (LISA)], was used to analyze the clusters of municipalities with the highest risk., Results: After smoothing the risk, the highest rates (over 50 per 100,000 inhabitants) were grouped in the eastern Mediterranean coastal areas and the north of the mainland, as well as in the Mediterranean islands. Moran's index smoothed rates were 0.15 for men and 0.23 for women. The spatial clusters of statistically significant higher rates calculated by the LISA index were distributed in the north and east for both sexes., Conclusions: These methods of spatial analysis allow patterns of disease distribution to be identified. All the methods used yielded similar results. These techniques are a complementary tool for epidemiological surveillance of infectious diseases., (Copyright © 2010 SESPAS. Published by Elsevier Espana. All rights reserved.)

Background: Tuberculosis incidence has been associated with many factors, both epidemiological and social. In Spain, tuberculosis is a statutorily notifiable disease requiring individualised reporting. During the last few years rates of respiratory tuberculosis show a steady decline. This study sought to assess respiratory tuberculosis morbidity and mortality in association to socio-economic and epidemiological covariates and estimate its spatial distribution across the country, using geo-statistical methods., Methods: Respiratory tuberculosis incidence rates were standardised by age and sex with the data of the National Epidemiological Surveillance Network (RENAVE, Red Nacional de Vigilancia Epidemiológica) for 2006. The following socio-economic variables were included in the study: socio-economic status, educational level, overcrowding rate, population density, standardised immigration rate by sex, unemployment rate and average spending per person in euros. The epidemiological variables included were, such as, AIDS rate and the influenza incidence rate. To assess the association of covariables a multivariate analysis was performed using a Generalised Linear Model assuming Poisson distribution. The goestatistical method co-kriging was adjusted with the significant variables to built the spatial distribution of risk., Results: The statistically significant covariates were overcrowding rate, standardised immigration rate by sex, educational level, unemployment rate, average spending per person in euros, AIDS rate and the influenza incidence rate. The geostatistical method shows spatial variability of the risk with higher risks in the northwest and southeast of the peninsula., Conclusion: Results prove that the co-kriging method is a useful tool to show the spatial distribution of risk. Alternatively, tuberculosis is associated with both social and epidemiological covariates.

Background: Oesophageal carcinoma is one of the most common cancers worldwide. Its incidence and mortality rates show a wide geographical variation at a world and regional level. Geographic mapping of age-standardized, cause-specific death rates at a municipal level could be a helpful and powerful tool for providing clues leading to a better understanding of its aetiology., Methods: This study sought to describe the geographic distribution of oesophageal cancer mortality for Spain's 8077 towns, using the autoregressive spatial model proposed by Besag, York and Mollié. Maps were plotted, depicting standardised mortality ratios, smoothed relative risk (RR) estimates, and the spatial pattern of the posterior probability of RR being greater than 1., Results: Important differences associated with area of residence were observed in risk of dying from oesophageal cancer in Spain during the study period (1989-1998). Among men, excess risk appeared across the north of the country, along a band spanning the length of the Cantabrian coastline, Navarre, the north of Castile & León and the north-west of La Rioja. Excess risk was likewise observed in the provinces of Cadiz and part of Seville in Andalusia, the islands of Tenerife and Gran Canaria, and some towns in the Barcelona and Gerona areas. Among women, there was a noteworthy absence of risk along the mid-section of the Cantabrian seaboard, and increases in mortality, not observed for men, in the west of Extremadura and south-east of Andalusia., Conclusion: These major gender- and area-related geographical differences in risk would seem to reflect differences in the prevalence of some well-established and modifiable risk factors, including smoking, alcohol consumption, obesity and diet. In addition, excess risks were in evidence for both sexes in some areas, possibly suggesting the implication of certain local environmental or socio-cultural factors. From a public health standpoint, small-area studies could be very useful for identifying locations where epidemiological research and intervention measures ought to receive priority, given the potential for reducing risk in certain places.

Background: Thyroid cancer is a tumor with a low but growing incidence in Spain. This study sought to depict its spatial municipal mortality pattern, using the classic model proposed by Besag, York and Mollié., Methods: It was possible to compile and ascertain the posterior distribution of relative risk on the basis of a single Bayesian spatial model covering all of Spain's 8077 municipal areas. Maps were plotted depicting standardized mortality ratios, smoothed relative risk (RR) estimates, and the posterior probability that RR > 1., Results: From 1989 to 1998 a total of 2,538 thyroid cancer deaths were registered in 1,041 municipalities. The highest relative risks were mostly situated in the Canary Islands, the province of Lugo, the east of La Coruña (Corunna) and western areas of Asturias and Orense., Conclusion: The observed mortality pattern coincides with areas in Spain where goiter has been declared endemic. The higher frequency in these same areas of undifferentiated, more aggressive carcinomas could be reflected in the mortality figures. Other unknown genetic or environmental factors could also play a role in the etiology of this tumor.