ABSTRACT
OBJETIVO: El consumo de tabaco es uno de los principales factores de riesgo evitables para el desarrollo de cáncer. El objetivo de este estudio es describir la frecuencia, la tendencia y la distribución geográfica de la incidencia de los tumores asociados al tabaco en el Área de Salud de León. MATERIAL Y MÉTODOS: Estudio observacional, descriptivo, que recoge los tumores asociados al consumo de tabaco del Registro Hospitalario de Tumores del Complejo Asistencial Universitario de León, entre 1997 y 2014 en residentes del Área de Salud de León. Se calcularon tasas brutas y ajustadas por trienios. Para el análisis de la distribución espacial se estimaron los riesgos relativos municipales suavizados mediante el ajuste del modelo de Besag, York y Mollié y sus probabilidades posteriores de que los riesgos relativos fuesen mayores de 1, utilizando métodos bayesianos. RESULTADOS: Se incluyeron 7.103 casos. Las tasas de incidencia brutas ascendieron de 116,4 (1997-1999) a 228,0 (2012-2014) por 100.000 hombres y de 19,8 (1997-1999) a 44,5 (2012-2014) por 100.000 mujeres. Las tasas ajustadas a población europea también ascendieron de 116,2 (1997-1999) a 136,9 (2012-2014) por 100.000 hombres y de 11 (1997-1999) a 24,5 (2012-2014) por 100.000 mujeres. En la zona sur y centro de la provincia son más frecuentes los municipios con riesgos relativos altos, varios de ellos superiores a 2 con unas probabilidades posteriores de 1. CONCLUSIONES: Los casos de tumores asociados al tabaco aumentaron en los trienios estudiados, especialmente en las mujeres. La diferente distribución geográfica puede ser utilizada como herramienta de prevención del consumo de tabaco en las áreas implicadas
OBJECTIVE: For cancer incidence, tobacco use is one of the main avoidable risk factors. The aim of this study is to describe the frequency, trend and geographical distribution of the incidence of tobacco-associated tumours in the León Health Area, Spain. MATERIAL AND METHODS: An observational, descriptive study was carried out on tumours of Hospital Registry of Tumours of the University Hospital Complex of León between 1997 and 2014. León Health Area residents, associated with smoking were included. Gross and adjusted rates were calculated and adjusted for triennials. For the analysis of spatial distribution, municipal relative hazards were smoothed by adjusting the Besag, York, and Mollié model and for their posterior probabilities for relative hazards to be higher than 1, using Bayesian methods. RESULTS: A total of 7,103 cases were included. Crude incidence rates rose from 116.4 (1997-1999) to 228.0 (2012-2014) per 100,000 men, and from 19.8 (1997-1999) to 44.5 (2012-2014) per 100,000 women. The adjusted rates for the European population also increased from 116.2 (1997-1999) to 136.9 (2012-2014) per 100,000 men, and from 11 (1997-1999) to 24.5 (2012-2014) per 100,000 women. In the south and centre of the province, there were municipalities with high relative hazards, several of them higher than 2 with posterior probabilities of 1. CONCLUSIONS: Tumours associated with tobacco increased in the triennial studied, especially in women. The different geographical distribution can be used as a tool to prevent tobacco consumption in the areas involved
Subject(s)
Humans , Male , Female , Middle Aged , Aged , Aged, 80 and over , Neoplasms/epidemiology , Tobacco Smoking/epidemiology , Incidence , Neoplasms/etiology , Registries , Risk Factors , Sex Distribution , Spain/epidemiology , Tobacco Smoking/adverse effectsABSTRACT
OBJECTIVE: For cancer incidence, tobacco use is one of the main avoidable risk factors.The aim of this study is to describe the frequency, trend and geographical distribution of the incidence of tobacco-associated tumours in the León Health Area, Spain. MATERIAL AND METHODS: An observational, descriptive study was carried out on tumours of Hospital Registry of Tumours of the University Hospital Complex of León between 1997 and 2014. León Health Area residents, associated with smoking were included. Gross and adjusted rates were calculated and adjusted for triennials. For the analysis of spatial distribution, municipal relative hazards were smoothed by adjusting the Besag, York, and Mollié model and for their posterior probabilities for relative hazards to be higher than 1, using Bayesian methods. RESULTS: A total of 7,103 cases were included. Crude incidence rates rose from 116.4 (1997-1999) to 228.0 (2012-2014) per 100,000 men, and from 19.8 (1997-1999) to 44.5 (2012-2014) per 100,000 women. The adjusted rates for the European population also increased from 116.2 (1997-1999) to 136.9 (2012-2014) per 100,000 men, and from 11 (1997-1999) to 24.5 (2012-2014) per 100,000 women. In the south and centre of the province, there were municipalities with high relative hazards, several of them higher than 2 with posterior probabilities of 1. CONCLUSIONS: Tumours associated with tobacco increased in the triennial studied, especially in women. The different geographical distribution can be used as a tool to prevent tobacco consumption in the areas involved.
Subject(s)
Neoplasms/epidemiology , Tobacco Smoking/epidemiology , Aged , Aged, 80 and over , Female , Humans , Incidence , Male , Middle Aged , Neoplasms/etiology , Registries , Risk Factors , Sex Distribution , Spain/epidemiology , Tobacco Smoking/adverse effectsABSTRACT
Introducción. La pandemia de la obesidad junto con la pandemia de gripe puede dar lugar a una importante carga de enfermedad. El índice de masa corporal (IMC) no correlaciona adecuadamente con el porcentaje de grasa corporal. El CUN-BAE es un estimador de grasa corporal para caucásicos que incluye el IMC, el sexo y la edad. El objeto de este trabajo es valorar la fracción atribuible poblacional de ingreso hospitalario por gripe debido a la grasa corporal medida con el IMC y el CUN-BAE. Metodología. Estudio multicéntrico de casos y controles. Los casos fueron ingresos hospitalarios con confirmación de gripe por PCR-RT entre 2009-2011. Empleando IMC o CUN-BAE, para cada categoría de adiposidad se calculó el riesgo de hospitalización por gripe mediante regresión logística condicional, y se estimó la fracción atribuible poblacional en el total de la muestra, en no vacunados y en menores de 65 años. Resultados. Se incluyeron 472 casos hospitalizados y 493 controles. La ORa de hospitalización por gripe, en comparación con el normopeso, se incrementó con cada nivel de IMC (ORa=1,26; 2,06 y 11,64) y de CUN-BAE (ORa=2,78; 4,29; 5,43 y 15,18). La fracción atribuible poblacional de hospitalización por gripe del CUN-BAE fue 3 veces superior que la estimada con el IMC (0,72 vs. 0,27), siendo similares las diferencias encontradas en no vacunados y en menores de 65 años. Conclusión. El IMC podría estar infraestimando la carga de enfermedad atribuible a la obesidad en la hospitalización por gripe. Se debería valorar adecuadamente el impacto de la obesidad y los criterios de recomendación vacunal
Introduction. The obesity pandemic together with the influenza pandemic could lead to a significant burden of disease. The body mass index (BMI) does not discriminate obesity appropriately. The CUN-BAE has recently been used as an estimate of body fatness for Caucasians, including BMI, gender, and age. The aim of this study is to assess the population attributable fraction of hospital admissions due to influenza, due to the body fatness measured with the BMI, and the CUN-BAE. Methods. A multicentre study was conducted using matched case-controls. Cases were hospital admissions with the influenza confirmed by the RT-PCR method between 2009 and 2011. The risk of hospital admission and the population attribuible fraction were calculated using the BMI or the CUN-BAE for each adiposity category in a conditional logical regression analysis adjusted for confounding variables. The analyzes were estimated in the total sample, in unvaccinated people, and those less than 65 years-old. Results. A total of 472 hospitalised cases and 493 controls were included in the study. Compared to normal weight, the aOR of influenza hospital admissions increases with each level of BMI (aOR=1.26; 2.06 and 11.64) and CUN-BAE (aOR=2.78; 4.29; 5.43 and 15.18). The population attributable fraction of influenza admissions using CUN-BAE is 3 times higher than that estimated with BMI (0,72 vs. 0,27), with the differences found being similar the non-vaccinated and under 65 year-olds. Conclusion. The BMI could be underestimating the burden of disease attributable to obesity in individuals hospitalised with influenza. There needs to be an appropriate assessment of the impact of obesity and vaccine recommendation criteria
Subject(s)
Humans , Male , Female , Middle Aged , Obesity/complications , Influenza, Human/diagnosis , Body Mass Index , Case-Control Studies , Adiposity/physiology , Logistic ModelsABSTRACT
INTRODUCTION: The obesity pandemic together with the influenza pandemic could lead to a significant burden of disease. The body mass index (BMI) does not discriminate obesity appropriately. The CUN-BAE has recently been used as an estimate of body fatness for Caucasians, including BMI, gender, and age. The aim of this study is to assess the population attributable fraction of hospital admissions due to influenza, due to the body fatness measured with the BMI, and the CUN-BAE. METHODS: A multicentre study was conducted using matched case-controls. Cases were hospital admissions with the influenza confirmed by the RT-PCR method between 2009 and 2011. The risk of hospital admission and the population attribuible fraction were calculated using the BMI or the CUN-BAE for each adiposity category in a conditional logical regression analysis adjusted for confounding variables. The analyzes were estimated in the total sample, in unvaccinated people, and those less than 65 years-old. RESULTS: A total of 472 hospitalised cases and 493 controls were included in the study. Compared to normal weight, the aOR of influenza hospital admissions increases with each level of BMI (aOR=1.26; 2.06 and 11.64) and CUN-BAE (aOR=2.78; 4.29; 5.43 and 15.18). The population attributable fraction of influenza admissions using CUN-BAE is 3 times higher than that estimated with BMI (0,72 vs. 0,27), with the differences found being similar the non-vaccinated and under 65 year-olds. CONCLUSION: The BMI could be underestimating the burden of disease attributable to obesity in individuals hospitalised with influenza. There needs to be an appropriate assessment of the impact of obesity and vaccine recommendation criteria.
