A longitudinal study of environmental tobacco smoke exposure in children: parental self reports versus age dependent biomarkers.

BACKGROUND: Awareness of the negative effects of smoking on children's health prompted a decrease in the self-reporting of parental tobacco use in periodic surveys from most industrialized countries. Our aim is to assess changes between ETS exposure at the end of pregnancy and at 4 years of age determined by the parents' self-report and measurement of cotinine in age related biological matrices. METHODS: The prospective birth cohort included 487 infants from Barcelona city (Spain). Mothers were asked about maternal and household smoking habit. Cord serum and children's urinary cotinine were analyzed in duplicate using a double antibody radioimmunoassay. RESULTS: At 4 years of age, the median urinary cotinine level in children increased 1.4 or 3.5 times when father or mother smoked, respectively. Cotinine levels in children's urine statistically differentiated children from smoking mothers (Geometric Mean (GM) 19.7 ng/ml; 95% CI 16.83-23.01) and exposed homes (GM 7.1 ng/ml; 95% CI 5.61-8.99) compared with non-exposed homes (GM 4.5 ng/ml; 95% CI 3.71-5.48). Maternal self-reported ETS exposure in homes declined in the four year span between the two time periods from 42.2% to 31.0% (p < 0.01). Nevertheless, most of the children considered non-exposed by their mothers had detectable levels of cotinine above 1 ng/mL in their urine. CONCLUSION: We concluded that cotinine levels determined in cord blood and urine, respectively, were useful for categorizing the children exposed to smoking and showed that a certain increase in ETS exposure during the 4-year follow-up period occurred.

[Discrete-event simulation models in the economic evaluation of health technologies and health products]. / Los modelos de simulación de eventos discretos en la evaluación económica de tecnologías y productos sanitarios.

The use of mathematical models to assess therapeutic alternatives is increasing in the economic evaluation of health technologies and services and these models are becoming an increasingly important aid to decision making in health care. Until now, 2 types of model have been used, depending to some extent on the disease to be studied: decision trees have been used for acute diseases and Markov models in chronic or recurrent diseases. However, both models present major limitations when addressing complex processes or diseases. Consequently, interest in, and the use of, discrete-event simulation is growing. The present article aims to describe the main characteristics of discrete-event simulation, the state of the art in this field, and the advantages of these models with respect to other kinds of models in health economics, especially in the evaluation of health technologies and product assessment.

Assessment of foetal exposure to cigarette smoke after recent implementations of smoke-free policy in Italy.

AIM: We investigated foetal exposure to cigarette smoke following maternal active and passive smoking at the end of the pregnancy in a cohort of mother-infant dyads after recent implementation of the Italian smoke-free legislation and information campaigns against smoking. METHODS: Study subjects were 979 mothers and their newborns attended at one of the major Florence hospitals between the end of 2004 and during 2005, when smoking banning legislation in all the enclosed places of employment was completely enforced. A structured questionnaire was completed by mothers and cord serum cotinine was used as a biomarker of foetal exposure to maternal smoke at the end of the pregnancy. RESULTS: Women (53.9%) declared to be non-smokers not exposed to environmental tobacco smoke (ETS), 33.5% to be exposed non-smokers, while 12.6% reported daily smoking during pregnancy. Based on the levels of cord serum cotinine, 78.9% newborns were not exposed to ETS, 13.5% were exposed to ETS and 7.7% were exposed to active maternal smoke. CONCLUSIONS: Smoke-free policies can be an effective strategy for reducing both first-hand and second-hand exposure to cigarette smoke in pregnant women and their newborns. Due to the implementation of smoke-free legislation and information campaigns against smoking, a significant trend towards less active smoking during pregnancy was observed in our study cohort, as well as a minimal exposure to ETS in non-smoking pregnant women and their newborns.

Prevalence of gestational exposure to cannabis in a Mediterranean city by meconium analysis.

AIM: To investigate the prevalence of in utero exposure to cannabis in a cohort of 974 mother-infants dyads from Barcelona (Spain). METHODS: A validated gas chromatographic-mass spectrometric assay was used for meconium analysis. RESULTS: Prenatal exposure to cannabis was detected in 5.3% newborns; however, only 1.7% of the participating mothers disclosed gestational drug use. Ethnicity was not associated with cannabis use, nor were the maternal features or newborns somatometry. A significantly higher percentage of cannabis using mothers had a managerial professional job versus nonusers. CONCLUSIONS: Meconium analysis is especially important to identify neonates who have been exposed to cannabis in utero, which appear normal at birth and therefore may not be recognized. Timely detection of these newborns at risk provides the basis for appropriate treatment and adequate medical and social follow-up.

Fetal exposure to cocaine and infections during the first 18 months of life in infants from a Mediterranean city.

AIM: The incidence of infections during the first 18 months of life was investigated in 36 infants prenatally exposed to cocaine and in 72 non-exposed controls from Barcelona, Spain. METHODS: Fetal exposure to cocaine was ascertained by meconium analysis, infections by structured questionnaire. RESULTS: A higher incidence of infections, if excluding those acquired in utero, was not found in exposed infants versus non-exposed infants of similar demographical and socioeconomic characteristics. CONCLUSIONS: A possible role for life style factor in those cases where increased infections are associated with fetal exposure to cocaine is hypothesized.

Los modelos de simulación de eventos discretos en la evaluación económica de tecnologías y productos sanitarios / Discrete-event simulation models in the economic evaluation of health technologies and health products

El uso de modelos matemáticos como instrumentos de evaluación de alternativas está teniendo una importancia cada vez mayor en el terreno de la evaluación económica de servicios y tecnologías sanitarias, con un papel cada vez más relevante como ayuda en la toma de decisiones en la gestión sanitaria. Hasta ahora se han usado fundamentalmente 2 tipos de modelos, en parte en función de la enfermedad estudiada. De esta forma, los árboles de decisión han sido muy utilizados para las enfermedades de carácter agudo y los modelos de Markov han sido usados en enfermedades crónicas o que presentan estados de salud recurrentes. Sin embargo, tanto unos como otros presentan importantes limitaciones a la hora de modelar de forma realista ciertos procesos o enfermedades, y por ello está creciendo el interés y el uso de los modelos de simulación de eventos discretos. El objetivo del presente artículo es describir las principales características que presentan los modelos de simulación de eventos discretos, describir las últimas novedades, así como presentar qué ventajas aportan con respecto a los otros tipos de modelos en economía de la salud y, especialmente, en la evaluación económica de tecnologías y productos sanitarios (AU)

The use of mathematical models to assess therapeutic alternatives is increasing in the economic evaluation of health technologies and services and these models are becoming an increasingly important aid to decision making in health care. Until now, 2 types of model have been used, depending to some extent on the disease to be studied: decision trees have been used for acute diseases and Markov models in chronic or recurrent diseases. However, both models present major limitations when addressing complex processes or diseases. Consequently, interest in, and the use of, discrete-event simulation is growing. The present article aims to describe the main characteristics of discrete-event simulation, the state of the art in this field, and the advantages of these models with respect to other kinds of models in health economics, especially in the evaluation of health technologies and product assessment (AU)