39 resultados para Switching regression models
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Background: There is growing evidence that traffic-related air pollution reduces birth weight. Improving exposure assessment is a key issue to advance in this research area.Objective: We investigated the effect of prenatal exposure to traffic-related air pollution via geographic information system (GIS) models on birth weight in 570 newborns from the INMA (Environment and Childhood) Sabadell cohort.Methods: We estimated pregnancy and trimester-specific exposures to nitrogen dioxide and aromatic hydrocarbons [benzene, toluene, ethylbenzene, m/p-xylene, and o-xylene (BTEX)] by using temporally adjusted land-use regression (LUR) models. We built models for NO2 and BTEX using four and three 1-week measurement campaigns, respectively, at 57 locations. We assessed the relationship between prenatal air pollution exposure and birth weight with linear regression models. We performed sensitivity analyses considering time spent at home and time spent in nonresidential outdoor environments during pregnancy.Results: In the overall cohort, neither NO2 nor BTEX exposure was significantly associated with birth weight in any of the exposure periods. When considering only women who spent < 2 hr/day in nonresidential outdoor environments, the estimated reductions in birth weight associated with an interquartile range increase in BTEX exposure levels were 77 g [95% confidence interval (CI), 7–146 g] and 102 g (95% CI, 28–176 g) for exposures during the whole pregnancy and the second trimester, respectively. The effects of NO2 exposure were less clear in this subset.Conclusions: The association of BTEX with reduced birth weight underscores the negative role of vehicle exhaust pollutants in reproductive health. Time–activity patterns during pregnancy complement GIS-based models in exposure assessment.
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Background: Few studies have used longitudinal ultrasound measurements to assess the effect of traffic-related air pollution on fetal growth.Objective: We examined the relationship between exposure to nitrogen dioxide (NO2) and aromatic hydrocarbons [benzene, toluene, ethylbenzene, m/p-xylene, and o-xylene (BTEX)] on fetal growth assessed by 1,692 ultrasound measurements among 562 pregnant women from the Sabadell cohort of the Spanish INMA (Environment and Childhood) study.Methods: We used temporally adjusted land-use regression models to estimate exposures to NO2 and BTEX. We fitted mixed-effects models to estimate longitudinal growth curves for femur length (FL), head circumference (HC), abdominal circumference (AC), biparietal diameter (BPD), and estimated fetal weight (EFW). Unconditional and conditional SD scores were calculated at 12, 20, and 32 weeks of gestation. Sensitivity analyses were performed considering time–activity patterns during pregnancy.Results: Exposure to BTEX from early pregnancy was negatively associated with growth in BPD during weeks 20–32. None of the other fetal growth parameters were associated with exposure to air pollution during pregnancy. When considering only women who spent 2 hr/day in nonresidential outdoor locations, effect estimates were stronger and statistically significant for the association between NO2 and growth in HC during weeks 12–20 and growth in AC, BPD, and EFW during weeks 20–32.Conclusions: Our results lend some support to an effect of exposure to traffic-related air pollutants from early pregnancy on fetal growth during mid-pregnancy.
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Background: Analyzing social differences in the health of adolescents is a challenge. The accuracy of adolescent's report on familial socio-economic position is unknown. The aims of the study were to examine the validity of measuring occupational social class and family level of education reported by adolescents aged 12 to 18, and the relationship between social position and self-reported health.Methods: A sample of 1453 Spanish adolescents 12 to 18 years old from urban and rural areas completed a self-administered questionnaire including the Child Health and Illness Profile-Adolescent Edition (CHIP-AE), and data on parental occupational social class (OSC) and level of education (LE). The responsible person for a sub-sample of teenagers (n = 91) were interviewed by phone. Kappa coefficients were estimated to analyze agreement between adolescents and proxy-respondents, and logistic regression models were adjusted to analyze factors associated with missing answers and disagreements. Effect size (ES) was calculated to analyze the relationship between OSC, LE and the CHIP-AE domain scores.Results: Missing answers were higher for father's (24.2%) and mother's (45.7%) occupational status than for parental education (8.4%, and 8.1% respectively), and belonging to a non-standard family was associated with more incomplete reporting of social position (OR = 4,98; 95%CI = 1,3–18,8) as was agreement between a parent and the adolescent. There were significant social class gradients, most notably for aspects of health related to resilience to threats to illness.ConclusionAdolescents can acceptably self-report on family occupation and level of education. Social class gradients are present in important aspects of health in adolescents.
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The paper examines the relationship between family formation (i.e., living with a partner and having children) and women’s occupational career in southern Europe (i.e., Greece, Italy, Portugal and Spain). The relationship is explored by analysing the impact that different family structures and male [nvolvement in caring activities have on women’s early occupational trajectories (i.e., remaining in the same occupational status, experiencing downward or upward mobility, or withdrawing from paid work). This research shows that male involvement in caring activities does not really push women ahead in their career, but the absolute lack of male support seems to negatively affect women’s permanence in paid work. These results apply to all southern European countries except Portugal, where the absolute absence of the partners’ support in caring activities does not seem to alter women’s determination to remain in paid work. The methodology applied consists of the estimation of multinomial logit regression models and the analysis is based on eight waves (1994-2001) of the European Community Household Panel (ECHP).
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Aim: To describe changes in leisure time and occupational physical activity status in an urban Mediterranean population-based cohort, and to evaluate sociodemographic, health-related and lifestyle correlates of such changes. Methods: Data for this study come from the Cornellè Health Interview Survey Follow-Up Study, a prospective cohort study of a representative sample (n¿=¿2500) of the population. Participants in the analysis reported here include 1246 subjects (567 men and 679 women) who had complete data on physical activity at the 1994 baseline survey and at the 2002 follow-up. We fitted Breslow-Cox regression models to assess the association between correlates of interest and changes in physical activity. Results: Regarding leisure time physical activity, 61.6% of cohort members with ¿sedentary¿ habits in 1994 changed their status to ¿light/moderate¿ physical activity in 2002, and 70% who had ¿light/moderate¿ habits in 1994 did not change their activity level. Regarding occupational physical activity, 74.4% of cohort members who were ¿active¿ did not change their level of activity, and 64.3% of participants with ¿sedentary¿ habits in 1994 changed to ¿active¿ occupational physical activity. No clear correlates of change in physical activity were identified in multivariate analyses. Conclusion: While changes in physical activity are evident in this population-based cohort, no clear determinants of such changes were recognised. Further longitudinal studies including other potential individual and contextual determinants are needed to better understand determinants of changes in physical activity at the population level.
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Work-related flow is defined as a sudden and enjoyable merging of action and awareness that represents a peak experience in the daily lives of workers. Employees" perceptions of challenge and skill and their subjective experiences in terms of enjoyment, interest and absorption were measured using the experience sampling method, yielding a total of 6981 observations from a sample of 60 employees. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes. According to the R2, AICc and BIC indexes, the nonlinear dynamical systems model (i.e. cusp catastrophe model) fit the data better than the linear and logistic regression models. Likewise, the cusp catastrophe model appears to be especially powerful for modelling those cases of high levels of flow. Overall, flow represents a nonequilibrium condition that combines continuous and abrupt changes across time. Research and intervention efforts concerned with this process should focus on the variable of challenge, which, according to our study, appears to play a key role in the abrupt changes observed in work-related flow.
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Brain oxidative processes play a major role in age-related cognitive decline, thus consumption of antioxidant-rich foods might help preserve cognition. Our aim was to assess whether consumption of antioxidant-rich foods in the Mediterranean diet relates to cognitive function in the elderly. In asymptomatic subjects at high cardiovascular risk (n = 447; 52% women; age 5580 y) enrolled in the PREDIMED study, a primary prevention dietary-intervention trial, we assessed food intake and cardiovascular risk profile, determined apolipoprotein E genotype, and used neuropsychological tests to evaluate cognitive function.We also measured urinary polyphenols as an objective biomarker of intake. Associations between energy-adjusted food consumption, urinary polyphenols, and cognitive scores were assessed by multiple linear regression models adjusted for potential confounders. Consumption of some foods was independently related to better cognitive function. The specific associations [regression coefficients (95% confidence intervals)] were: total olive oil with immediate verbal memory [0.755 (0.1511.358)]; virgin olive oil and coffee with delayed verbal memory [0.163 (0.0100.316) and 0.294 (0.0550.534), respectively];walnuts with working memory [1.191 (0.0612.322)]; and wine with Mini-Mental State Examination scores [0.252 (0.0060.496)]. Urinary polyphenols were associated with better scores in immediate verbal memory [1.208 (0.2362.180)]. Increased consumption of antioxidant-rich foods in general and of polyphenols in particular is associated with better cognitive performance in elderly subjects at high cardiovascular risk. The results reinforce the notion that Mediterranean diet components might counteract age-related cognitive decline.
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Different components of global change can have interacting effects on biodiversity and this may influence our ability to detect the specific consequences of climate change through biodiversity indicators. Here, we analyze whether climate change indicators can be affected by land use dynamics that are not directly determined by climate change. To this aim, we analyzed three community-level indicators of climate change impacts that are based on the optimal thermal environment and averagelatitude of the distribution of bird species present at local communities. We used multiple regression models to relate the variation in climate change indicators to: i) environmental temperature; and ii) three landscape gradients reflecting important current land use change processes (land abandonment, fire impacts and urbanization), all of them having forest areas at their positive extremes. We found that, with few exceptions, landscape gradients determined the figures of climate change indicators as strongly as temperature. Bird communities in forest habitats had colder-dwelling bird species with more northerndistributions than farmland, burnt or urban areas. Our results show that land use changes can reverse, hide or exacerbate our perception of climate change impacts when measured through community-level climate change indicators. We stress the need of an explicit incorporation of the interactions between climate change and land use dynamics to understand what are current climate change indicators indicating and be able to isolate real climate change impacts
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This study aimed to test subjective indicators designed to analyze the role food plays in children’s lives, explore children’s personal well-being, and evaluate the relationship between these two phenomena. It was conducted on 371 children aged 10 to 12 by means of a selfadministered questionnaire. Results showed a marked interest in food on the part of children, who consider taste and health the most important indicators when it comes to eating. They demonstrated a high level of personal well-being, measured using Cummins & Lau’s adapted version of the Personal Well- Being Index–School Children (PWI-SC) (2005), overall life satisfaction (OLS) and satisfaction with various life domains (friends, family, sports, food and body). Regression models were conducted to explain satisfaction with food, taking as independent variables the interest children have in food, the importance they give to different reasons for eating, scores from the PWI-SC, OLS and satisfaction with various life domains. In the final model, it was found that OLS, health indicators, satisfaction with health from the PWI-SC and satisfaction with your body contribute to explaining satisfaction with food. The results obtained suggest that satisfaction with food is a relevant indicator in the exploration of children’s subjective well-being, calling into question the widespread belief that these aspects are of exclusive interest to adults. They also seem to reinforce the importance of including food indicators in any study aimed at exploring the well-being of the 10 to 12 year-old population.
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The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.
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Background During the 2009 influenza pandemic, a change in the type of patients most often affected by influenza was observed. The objective of this study was to assess the role of individual and social determinants in hospitalizations due to influenza A (H1N1) 2009 infection. Methods We studied hospitalized patients (cases) and outpatients (controls) with confirmed influenza A (H1N1) 2009 infection. A standardized questionnaire was used to collect data. Variables that might be related to the hospitalization of influenza cases were compared by estimation of the odds ratio (OR) and 95% confidence intervals (CI) and the variables entered into binomial logistic regression models. Results Hospitalization due to pandemic A (H1N1) 2009 influenza virus infections was associated with non-Caucasian ethnicity (OR: 2.18, 95% CI 1.17 − 4.08), overcrowding (OR: 2.84, 95% CI 1.20 − 6.72), comorbidity and the lack of previous preventive information (OR: 2.69, 95% CI: 1.50 − 4.83). Secondary or higher education was associated with a lower risk of hospitalization (OR 0.56, 95% CI: 0.36 − 0.87) Conclusions In addition to individual factors such as comorbidity, other factors such as educational level, ethnicity or overcrowding were associated with hospitalization due to A (H1N1) 2009 influenza virus infections.
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Background: There are few studies comparing pharmaceutical costs and the use of medications between immigrants and the autochthonous population in Spain. The objective of this study is to evaluate whether there are differences in pharmaceutical consumption and expenses between immigrant and Spanish-born populations. Methods: Prospective observational study in 1,630 immigrants and 4,154 Spanish-born individuals visited by fifteen primary care physicians at five public Primary Care Clinics (PCC) during 2005 in the city of Lleida, Catalonia (Spain). Data on pharmaceutical consumption and expenses was obtained from a comprehensive computerized data-collection system. Multinomial regression models were used to estimate relative risks and confidence intervals of pharmaceutical expenditure, adjusting for age and sex. Results: The percentage of individuals that purchased medications during a six-month period was 53.7% in the immigrant group and 79.2% in the autochthonous group. Pharmaceutical expenses and consumption were lower in immigrants than in autochthonous patients in all age groups and both genders. The relative risks of being in the highest quartile of expenditure, for Spanish-born versus immigrants, were 6.9, 95% CI = (4.2, 11.5) in men and 5.3, 95% CI = (3.5, 8.0) in women, with the reference category being not having any pharmaceutical expenditure. Conclusion: Pharmaceutical expenses are much lower for immigrants with respect to autochthonous patients, both in the percentage of prescriptions filled at pharmacies and the number of containers of medication obtained, as well as the prices of the medications used. Future studies should explore which factors explain the observed differences in pharmaceutical expenses and if these disparities produce health inequalities.
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Background: Characterizing and comparing the determinant of cotinine concentrations in different populations should facilitate a better understanding of smoking patterns and addiction. This study describes and characterizes determinants of salivary cotinine concentration in a sample of Spanish adult daily smoker men and women. Methods: A cross-sectional study was carried out between March 2004 and December 2005 in a representative sample of 1245 people from the general population of Barcelona, Spain. A standard questionnaire was used to gather information on active tobacco smoking and passive exposure, and a saliva specimen was obtained to determine salivary cotinine concentration. Two hundred and eleven adult smokers (>16 years old) with complete data were included in the analysis. Determinants of cotinine concentrations were assessed using linear regression models. Results: Salivary cotinine concentration was associated with the reported number of cigarettes smoked in the previous 24 hours (R2 = 0.339; p < 0.05). The inclusion of a quadratic component for number of cigarettes smoked in the regression analyses resulted in an improvement of the fit (R2 = 0.386; p < 0.05). Cotinine concentration differed significantly by sex, with men having higher levels. Conclusion: This study shows that salivary cotinine concentration is significantly associated with the number of cigarettes smoked and sex, but not with other smoking-related variables.
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Brain oxidative processes play a major role in age-related cognitive decline, thus consumption of antioxidant-rich foods might help preserve cognition. Our aim was to assess whether consumption of antioxidant-rich foods in the Mediterranean diet relates to cognitive function in the elderly. In asymptomatic subjects at high cardiovascular risk (n = 447; 52% women; age 55-80 y) enrolled in the PREDIMED study, a primary prevention dietary-intervention trial, we assessed food intake and cardiovascular risk profile, determined apolipoprotein E genotype, and used neuropsychological tests to evaluate cognitive function.We also measured urinary polyphenols as an objective biomarker of intake. Associations between energy-adjusted food consumption, urinary polyphenols, and cognitive scores were assessed by multiple linear regression models adjusted for potential confounders. Consumption of some foods was independently related to better cognitive function. The specific associations [regression coefficients (95% confidence intervals)] were: total olive oil with immediate verbal memory [0.755 (0.151-1.358)]; virgin olive oil and coffee with delayed verbal memory [0.163 (0.010-0.316) and 0.294 (0.055-0.534), respectively];walnuts with working memory [1.191 (0.061-2.322)]; and wine with Mini-Mental State Examination scores [0.252 (0.006-0.496)]. Urinary polyphenols were associated with better scores in immediate verbal memory [1.208 (0.236-2.180)]. Increased consumption of antioxidant-rich foods in general and of polyphenols in particular is associated with better cognitive performance in elderly subjects at high cardiovascular risk. The results reinforce the notion that Mediterranean diet components might counteract age-related cognitive decline.
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Abstract Purpose- There is a lack of studies on tourism demand forecasting that use non-linear models. The aim of this paper is to introduce consumer expectations in time-series models in order to analyse their usefulness to forecast tourism demand. Design/methodology/approach- The paper focuses on forecasting tourism demand in Catalonia for the four main visitor markets (France, the UK, Germany and Italy) combining qualitative information with quantitative models: autoregressive (AR), autoregressive integrated moving average (ARIMA), self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. The forecasting performance of the different models is evaluated for different time horizons (one, two, three, six and 12 months). Findings- Although some differences are found between the results obtained for the different countries, when comparing the forecasting accuracy of the different techniques, ARIMA and Markov switching regime models outperform the rest of the models. In all cases, forecasts of arrivals show lower root mean square errors (RMSE) than forecasts of overnight stays. It is found that models with consumer expectations do not outperform benchmark models. These results are extensive to all time horizons analysed. Research limitations/implications- This study encourages the use of qualitative information and more advanced econometric techniques in order to improve tourism demand forecasting. Originality/value- This is the first study on tourism demand focusing specifically on Catalonia. To date, there have been no studies on tourism demand forecasting that use non-linear models such as self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. This paper fills this gap and analyses forecasting performance at a regional level. Keywords Tourism, Forecasting, Consumers, Spain, Demand management Paper type Research paper