Factores de riesgo para el abandono del tratamiento antituberculoso esquema I y II Perú 2004

Antecedentes: El control de la tuberculosis es un complejo reto para la salud pública en el mundo que involucra asegurar el acceso al diagnóstico, tratamiento y cura de los pacientes. Se sabe que el no cumplimiento del tratamiento puede llevar a complicaciones fatales y a la emergencia de cepas resistentes. La identificación y el entendimiento de los factores que determinan el no cumplimiento del tratamiento, proveerán información para aumentar la eficacia de los programas de control. Objetivo: Identificar factores de riesgo para el abandono del tratamiento antituberculosis en el Perú. Material y métodos: Se realizó un estudio de casos y controles en las provincias de mayor incidencia de abandono de tratamiento durante el año 2004. Se seleccionaron 295 casos y 590 controles y la relación de casos a controles fue de 1:2 los factores relacionados al abandono de tratamiento, se evaluaron mediante análisis de riesgo. Resultados: Se identificó como factores de riesgo para el abandono el presentar una edad entre 15 y 20 años (OR=1.78/1.02-3.13) o mayor de 40 años (OR=1.68/1.12-2.51),el presentar un nivel de educación inferior: secundaria (OR=1.88/1.09-3.26), primaria (OR=2.46/1.24-4.86), así como presentar al menos 1 Necesidad Básica Insatisfecha (NBI) (OR=1.67/1.09-2.54), el considerar al personal capacitado a medias (OR=1.63/1.06-2.52), así como el presentar el antecedente de abandono anterior (OR=7.06/4.32-11.53), así como manifestar disconformidad con la información recibida por el personal: considerar elemental (regular) la información recibida (OR=3.64/1.11-11.88), mostrarse insatisfecho o muy insatisfecho con la información recibida (OR=5.38/1.33-21.73). Conclusiones Es evidente que a pesar que existen muchos factores reconocidos en la bibliografía como factores de riesgo para el abandono de tratamiento, luego del análisis con la regresión logística, son solamente nueve los factores que podrían considerarse factores pronósticos de abandono de tratamiento.Background: Tuberculosis control is a complex public health challenge in the world that involves ensuring access to diagnosis, treatment and cure of patients. It is known that no treatment compliance can lead to fatal complications and the emergence of resistant strains. The identification and understanding of the determinants of treatment noncompliance, provide information to enhance the effectiveness of control programs. Objective: To identify risk factors for noncompliance with tuberculosis treatment in Peru. Methods: We performed a case-control study in the provinces with the highest incidence of treatment noncompliance in 2004. We selected 295 cases and 590 controls and cases to controls ratio of 1:2 will be factors related to noncompliance of treatment were assessed by risk analysis. Results: We identified risk factors for noncompliance the present age from 15 to 20 years (OR = 1.78/1.02-3.13) or > 40 years (OR = 1.68/1.12-2.51), the present level of education Bottom: secondary (OR = 1.88/1.09-3.26), primary (OR = 2.46/1.24-4.86) and submit at least 1 unmet basic needs (NBI) (OR = 1.67/1.09-2.54), to consider personnel trained half (OR = 1.63/1.06-2.52) and presenting a history of previous of noncompliance (OR = 7.06/4.32-11.53), and to express disagreement with the information received by staff, to consider elementary (regular) information received (OR = 3.64/1.11-11.88), appear dissatisfied or very dissatisfied with the information received (OR = 5.38/1.33-21.73). Conclusions: It is evident that although there are many factors known in the literature as risk factors for discontinuing treatment after logistic regression analysis, are only nine factors that could be considered predictors of treatment dropout.Tesi

Epidemiología de la tuberculosis: características del abandono de tratamiento, hospitalizaciones y tuberculosis extrapulmonar

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Medicina Preventiva y Salud Pública y Microbiología. Fecha de lectura: 15-12-201

Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health

The objective of this study was to identify which air pollutants, atmospheric variables and health determinants could infuence COVID-19 mortality in Spain. This study used information from 41 of the 52 provinces in Spain (from Feb. 1, to May 31, 2021). Generalized Linear Models (GLM) with Poisson link were carried out for the provinces, using the Rate of Mortality due to COVID-19 (CM) per 1,000,000 inhabitants as dependent variables, and average daily concentrations of PM10 and NO2 as independent variables. Meteorological variables included maximum daily temperature (Tmax) and average daily absolute humidity (HA). The GLM model controlled for trend, seasonalities and the autoregressive character of the series. Days with lags were established. The relative risk (RR) was calculated by increases of 10 g/m3 in PM10 and NO2 and by 1 ℃ in the case of Tmax and 1 g/m3 in the case of HA. Later, a linear regression was carried out that included the social determinants of health.The authors would like to thank the Carlos III Health Institute for their fnancial support Project ENPY 221/20. This work was carried out with funds of the ENPY 221/20 project

Efectos de factores locales en la evolución de las temperaturas de mínima mortalidad en España (1983-2018)

Ponencia presentada en: XII Congreso de la Asociación Española de Climatología celebrado en Santiago de Compostela entre el 19 y el 21 de octubre de 2022.[ES]En la actualidad la Unión Europea se encuentra inmersa en decisiones políticas para combatir el cambio climático. Entre las medidas urgentes para abordar la emergencia climática se encuentran los planes y procesos claves para facilitar la adaptación a las altas temperaturas y reducir los efectos adversos en la salud de los habitantes. El objetivo de este estudio es conocer qué factores sociales, climáticos y económicos se han relacionado con la evolución de las temperaturas de mínima mortalidad (TMM) en España en los contextos rural y urbano, durante el periodo 1983-2018. Para ello, se estudiaron los factores locales en cuanto a su relación con los niveles de adaptación al calor.[EN]The European Union is currently engaged in policy decisions to combat climate change. Among the urgent measures to address the climate emergency are key plans and processes to facilitate adaptation to high temperatures and reduce adverse effects on people's health. The aim of this study was to provide knowledge related to the social, climate and economic factors that are related to the evolution of minimum mortality temperatures (MMT) in Spain in the rural and urban contexts, during the 1983–2018 time period. For this purpose, local factors were studied regarding their relationship to levels of adaptation to heat.Los autores agradecen las subvenciones para los proyectos ENPY107/18, ENPY 376/18 y ENPY 470/19 del Instituto de Salud Carlos III (ISCIII) con número de expediente ENPY 470/19, cuenta con el apoyo de la Fundación Biodiversidad, del Ministerio para la Transición Ecológica y el Reto Demográfico

Análisis de la vulnerabilidad al calor en zonas rurales y urbanas de España ¿qué factores pueden explicar su comportamiento geográfico?

Ponencia presentada en: XII Congreso de la Asociación Española de Climatología celebrado en Santiago de Compostela entre el 19 y el 21 de octubre de 2022.[ES]El objetivo de este estudio analizar la distinta vulnerabilidad al calor extremo entre poblaciones rurales y urbanas y determinar si este está determinado por variables socioeconómicas. Métodos: Estudio ecológico longitudinal y retrospectivo de series temporales, entre 01/01/2000 y 31/12/2013, en 42 áreas geográficas en 10 provincias de España. Primero, se determinó a partir de qué percentil de temperaturas estivales (Pthreshold)(junio-septiembre) se producen aumentos de mortalidad atribuibles a la ola de calor. Después, a partir de los Pthreshold se determinó la vulnerabilidad y analizó su distribución mediante modelos lineales mixtos de Poisson (link = log). En ellos, la variable dependiente fue la vulnerabilidad y las variables independientes la exposición a altas temperaturas, la aridez del clima, índice de privación, porcentaje de mayores de 65 años, índice de ruralidad, porcentaje de vivienda anterior a 1980 y estado de la vivienda.[EN]The aim of this study is to analyse the different vulnerability to extreme heat between rural and urban populations and to determine whether this is determined by socioeconomic variables. Methods: Longitudinal and retrospective ecological time series study, between 01/01/2000 and 31/12/2013, in 42 geographical areas in 10 provinces of Spain. First, we determined from which percentile of summer temperatures (Pthreshold) (June- September) mortality increases attributable to the heat wave occur. Then, from the Pthresholds, vulnerability was determined and its distribution analysed using Poisson linear mixed models (link = log). The dependent variable was vulnerability and the independent variables were exposure to high temperatures, climate aridity, deprivation index, percentage of people over 65 years old, rurality index, percentage of pre-1980 housing and housing condition

Effects of local factors on adaptation to heat in Spain (1983–2018)

The European Union is currently immersed in policy development to address the effects of climate change around the world. Key plans and processes for facilitating adaptation to high temperatures and for reducing the adverse effects on health are among the most urgent measures. Therefore, it is necessary to understand those factors that influence adaptation. The aim of this study was to provide knowledge related to the social, climate and economic factors that are related to the evolution of minimum mortality temperatures (MMT) in Spain in the rural and urban contexts, during the 1983–2018 time period. For this purpose, local factors were studied regarding their relationship to levels of adaptation to heat.The authors gratefully acknowledge the grants for projects ENPY107/18; ENPY 376/18, ENPY 470/19 and ENPY 340/20 from the Carlos III Institute of Health, and is supported by the Biodiversity Foundation of the Ministry for Ecological Transition and Demographic Challenge

Gender differences in adaptation to heat in Spain (1983–2018)

In Spain the average temperature has increased by 1.7 °C since pre-industrial times. There has been an increase in heat waves both in terms of frequency and intensity, with a clear impact in terms of population health. The effect of heat waves on daily mortality presents important territorial differences. Gender also affects these impacts, as a determinant that conditions social inequalities in health. There is evidence that women may be more susceptible to extreme heat than men, although there are relatively few studies that analyze differences in the vulnerability and adaptation to heat by sex. This could be related to physiological causes. On the other hand, one of the indicators used to measure vulnerability to heat in a population and its adaptation is the minimum mortality temperature (MMT) and its temporal evolution.The authors wish to thank the funding provided by the ENPY 304/20, ENPY 376/18 and ENPY 107/18 projects of the Carlos III Health Institute III (ISCIII)

Do Air Pollution and Meteorological Variables Have a Bearing on COVID-19 Mortality? Benchmarking of Time Series between the First and Second Waves in Nine Spanish Provinces

[ES] Algunos contaminantes como las PM10, el NO2 o el O3 tienen influencia en la salud de las personas, tal y como apuntan numerosos estudios al relacionarse con la mortalidad tanto a corto como a largo plazo. Se estudió una muestra de 9 de las 52 provincias españolas. Se realizaron modelos lineales generalizados (GLM) con link Poisson en los periodos de la primera y segunda ola entre los valores medios diarios de las variables independientes (PM10, NO2 y O3 como contaminantes atmosféricos y variables meteorológicas (temperatura máxima diaria y humedad absoluta)) y la variable dependiente (tasa de mortalidad por COVID-19, TMC) durante la primera y segunda ola. Entre las variables independientes y la dependiente se establecieron los retardos estadísticamente significativos (lag). A partir de los estimadores obtenidos en los GLM se calcularon los riesgos relativos asociados, por aumentos de 10 μg/m3 para los contaminantes atmosféricos, 1ºC para la temperatura máxima y 1 g/m3 para la humedad absoluta. Los resultados muestran que existe una mayor asociación del NO2 con la TMC que para el resto de los contaminantes atmosféricos. Las variables meteorológicas examinadas no han presentado una asociación robusta entre ambas olas, lo que indica un rol menor en relación a la TMC. En conclusión, la contaminación atmosférica por NO2 y PM10 presentan una asociación estadísticamente significativa con la TMC, aunque limitada y sub[EN] Some pollutants like PM10, NO2 and O3 are detrimental to people’s health, as numerous studies have shown, and they are related to short-term and long-term mortality. A sample of 9 out of the 52 Spanish provinces was studied. Generalized linear models (GLM) with a Poisson link function were developed during the time periods corresponding to the first and second waves of the daily average values of the independent variables (PM10, NO2 and O3, as atmospheric pollutants, and meteorological variables such as the daily maximum temperature and the absolute humidity) versus the dependent variable (COVID-19 mortality rate, or CMR) during said first and second waves. Statistically significant lags between the independent variables and the dependent variable were established. The associated relative risks were calculated from the estimators obtained in the GLMs, with increases of 10 μg/m3 for atmospheric pollutants, 1°C for the maximum temperature and 1 g/m3 for the absolute humidity. The results show that NO2 has a stronger relationship with the CMR than the other air pollutants. The meteorological variables examined did not show a robust relationship between both waves, which indicates that they played a minor role in the CMR. In conclusion, air pollutants such as to NO2 and PM10 had a statistically significant relationship with the CMR, although it is limited and subordinate to other factors such as the public health measures that were taken, the presence of comorbidities and the age of the patient.[PT] Alguns poluentes como as PM10, o NO2 ou o O3 têm influência na saúde das pessoas, como apontam numerosos estudos, pois estão relacionados com a mortalidade tanto a curto como a longo prazo. Foi estudada uma amostra de 9 das 52 províncias espanholas. Realizaram-se modelos lineares generalizados (GLM) com link Poisson nos períodos da primeira e segunda vagas entre os valores médios diários das variáveis independentes (PM10, NO2 e O3 como poluentes atmosféricos e temperatura máxima diária e humidade como condições meteorológicas) e da variável dependente (taxa de mortalidade por Covid-19, TMC) durante a primeira e segunda vagas. Entre as variáveis independentes e a dependente foram estabelecidos atrasos estatisticamente significativos (lag). A partir dos estimadores obtidos nos GLM calcularam-se os riscos relativos associados, para aumentos de 10 μg/m3 para poluentes atmosféricos, 1 °C para temperatura máxima e 1 g/m3 para humidade absoluta. Os resultados mostram que existe uma maior associação do NO2 com a TMC do que para o resto dos poluentes atmosféricos. As variáveis meteorológicas examinadas não apresentaram uma associação robusta entre ambas as vagas, o que indica um papel menor em relação à TMC. Em conclusão, a poluição atmosférica por NO2 e PM10 apresenta associação estatisticamente significativa com a TMC, embora seja limitada e subordinada a outros fatores como as medidas de saúde pública adotadas, a presença de comorbilidades e a idade do paciente