The impact of a cooking and gardening summer camp experience on the fruit and vegetable consumption of elementary school-aged children

Childhood obesity is a significant public health problem. Over 15 percent of children in the United States are obese, and about 25 percent of children in Texas are overweight (CDC NHANES). Furthermore, about 30 percent of elementary school aged children in Harris County, Texas are overweight or obese (Children at Risk Institute 2010). In addition to actions such as increasing physical activity, decreasing television watching and video game time, decreasing snacking on low nutrient calorie dense foods and sugar sweetened beverages, children need to consume more fruits and vegetables. According to the National Health and Nutrition Examination Survey (NHANES) from 2002, about 26 percent of U.S. children are meeting the recommendations for daily fruit intake and about 16 percent are meeting the recommendations for daily vegetable intake (CDC NHANES). In 2004, the average total intake of vegetables was 0.9 cups per day and 1.1 cups of fruit per day by children ages four to nine years old in the U.S. (CDC NHANES). Not only do children need effective nutrition education to learn about fruits and vegetables, they also need access and repeated exposure to fruits and vegetables (Anderson 2009, Briefel 2009). Nutrition education interventions that provide a structured, hands-on curriculum such as school gardens have produced significant changes in child fruit and vegetable intake (Blair 2009, McAleese 2007). To prevent childhood obesity from continuing into adolescence and adulthood, effective nutrition education interventions need to be implemented immediately and for the long-term. However, research has shown short-term nutrition education interventions such as summer camps to be effective for significant changes in child fruit and vegetable intake, preferences, and knowledge (Heim 2009). ^ A four week summer camp based on cooking and gardening was implemented at 6 Multi-Service centers in a large, urban city. The participants included children ranging in age from 7 to 14 years old (n=64). The purpose of the camp was to introduce children to their food from the seed to the plate through the utilization of gardening and culinary exercises. The summer camp activities were aimed at increasing the children's exposure, willingness to try, preferences, knowledge, and intake of fruits and vegetables. A survey was given on the first day of camp and again on the last day of camp that measured the pre- and post differences in knowledge, intake, willingness to try, and preferences of fruits and vegetables. The present study examined the short-term effectiveness of a cooking and garden-based nutrition education program on the knowledge, willingness, preferences, and intake among children aged 8 to 13 years old (n=40). The final sample of participants (n=40) was controlled for those who completed pre- and post-test surveys and who were in or above the third grade level. Results showed a statistically significant increase in the reported intake of vegetables and preferences for vegetables, specifically green beans, and fruits. There was also a significant increase in preferences for fruits among boys and participants ages 11 to 13 years. The results showed a change in the expected direction of willingness to try, preferences for vegetables, and intake of fruit, however these were not statistically significant. Interestingly, the results also showed a decrease in the intake of low nutrient calorie dense foods such as sweets and candy.^

Impact of traffic pollution on telomere length and chronic diseases: Results from the multi-ethnic study of atherosclerosis and the Mexican-American cohort study

Exposure to air pollutants in urban locales has been associated with increased risk for chronic diseases including cardiovascular disease (CVD) and pulmonary diseases in epidemiological studies. The exact mechanism explaining how air pollution affects chronic disease is still unknown. However, oxidative stress and inflammatory pathways have been posited as likely mechanisms. ^ Data from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Mexican-American Cohort Study (2003-2009) were used to examine the following aims, respectively: 1) to evaluate the association between long-term exposure to ambient particulate matter (PM) (PM10 and PM2.5) and nitrogen oxides (NO x) and telomere length (TL) among approximately 1,000 participants within MESA; and 2) to evaluate the association between traffic-related air pollution with self-reported asthma, diabetes, and hypertension among Mexican-Americans in Houston, Texas. ^ Our results from MESA were inconsistent regarding associations between long-term exposure to air pollution and shorter telomere length based on whether the participants came from New York (NY) or Los Angeles (LA). Although not statistically significant, we observed a negative association between long-term air pollution exposure and mean telomere length for NY participants, which was consistent with our hypothesis. Positive (statistically insignificant) associations were observed for LA participants. It is possible that our findings were more influenced by both outcome and exposure misclassification than by the absence of a relationship between pollution and TL. Future studies are needed that include longitudinal measures of telomere length as well as focus on effects of specific constituents of PM and other pollutant exposures on changes in telomere length over time. ^ This research provides support that Mexican-American adults who live near a major roadway or in close proximity to a dense street network have a higher prevalence of asthma. There was a non-significant trend towards an increased prevalence of adult asthma with increasing residential traffic exposure especially for residents who lived three or more years at their baseline address. Even though the prevalence of asthma is low in the Mexican-origin population, it is the fastest growing minority group in the U.S. and we would expect a growing number of Mexican-Americans who suffer from asthma in the future. Future studies are needed to better characterize risks for asthma associated with air pollution in this population.^

Metabolic syndrome in Mexican American females---prevalence and impact of age, socioeconomic status, and family history of type II diabetes

This thesis presents an analysis of data from Molecular Epidemiology of Type II Diabetes Mellitus in Mexican Americans. The study included 294 families. Among the participating families were 500 Mexican American females aged 19 to 86 who provided information on characteristics such as height, weight, and a variety of biochemical indicators. The research questions for this thesis are: (1) How strong is the association between indicators of the metabolic syndrome in study participants and their family histories of type II diabetes; and (2) How is an individual's family history of type II diabetes, age and socioeconomic status associated with the metabolic syndrome? In this thesis education status of the participants is used as an indicator of socioeconomic status. Answers to these questions are provided through the analysis of women's responses to written questionnaires and biochemical data. ^

The Impact of Title IV-E Training on Case Outcomes for Children Serviced by CPS

This study was designed to determine if the professional social work education provided by Title IV-E stipends leads to better case outcomes for children serviced by a southern state in the U.S. Desired case outcomes included lower levels of recurrence of child maltreatment, lower levels of foster care re-entries, greater stability of foster care placements, more reunifications with families within 12 months of placement in foster care, and more adoptions within 24 months of being placed in foster care. Data were obtained from the state’s case outcome records. The findings from the study indicate that Title IV-E stipend workers had significantly better outcomes than Non-Title IV-E workers in two areas: reunifications within twelve months and finalized adoptions within twenty-four months. In addition, non-Title IV-E workers with social work degrees were significantly more likely to achieve positive outcomes regarding recurrence of maltreatment, stability of foster care placement, and length of time to achieve adoption. The study recommends that state child protective service (CPS) agencies continue to offer Title IV-E child welfare training programs and hire degreed social workers. CPS should also continue to support the Title IV-E program and encourage employees to participate in the program. In addition, it is recommended that jobs be restructured to maximize activities that positively impact case outcomes and that the salaries of CPSworkers be increased. Additional research should also be conducted to contribute to a better understanding of other factors that positively impact case outcomes.

DEVELOPMENT OF NOVEL METHODS TO MINIMIZE THE IMPACT OF SEQUENCING ERRORS IN THE NEXT-GENERATION SEQUENCING DATA ANALYSIS

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

Long-term impact of a weight management summer camp on obese children

Background: interventions that focus on improving eating habits, increasing physical activity, and reducing sedentary behaviors on weight status and body mass index percentile and z-scores in youths have not been well documented. This study aimed to determine the short and long term effects of a 2-week residential weight management summer camp program for youths on weight, BMI, BMI percentile, and BMI z-score. ^ Methods: A sample of 73 obese multiethnic 10-14 years old youths (11.9 ± 1.4) attended a weight management camp called Kamp K'aana for two weeks and completed a 12-month follow-up on height and weight. As part of Kamp K'aana, participants received a series of nutrition, physical activity and behavioral lessons and were on an 1800 kcal per day meal plan. Anthropometric measurements of height and weight were taken to calculate participants' BMI percentiles and z-scores. Paired t-tests, chi square test and ANCOVA, adjusting for age, gender, and ethnicity were used to assess changes in body weight, BMI, BMI percentiles and BMI z-scores pre to two-weeks post-camp and 12 months post-camp. ^ Results: Significant reductions in body weight of 3.6 ± 1.4 (P = 0.0000), BMI of 1.4 ± 0.54 (P = 0.0000), BMI percentile of 0.45 ± 0.06 (P = 0.0000), and BMI z-score of 0.1 ± 0.06 (P = 0.0000) were observed at the end of the camp. Significant reductions in BMI z-scores (P < 0.001) and BMI percentile (P < 0.001) were observed at the 12-month reunion when compared to pre- and two-weeks post camp data. There was a significant increase in weight and BMI (P = 0.0000) at the 12-month reunion when compared to pre and post camp measurements. ^ Conclusion: Kamp K'aana has consistently shown short-term reductions in weight, BMI, BMI percentile, and BMI z-score. Results from analysis of long-term data suggest that this intervention had beneficial effects on body composition in an ethnically diverse population of obese children. Further research which includes a control group, larger sample size, and cost-analysis should be conducted.^

Impact of Liquid Swine Manure Application and Cover Crops on Ground Water Quality

The primary objective of this project was to determine the impact of appropriate rates of swine manure applications to corn and soybeans based on nitrogen and phosphorus requirements of crops, soil phosphorus accumulation, and the potential of nitrate and phosphorus leaching to groundwater. Another purpose of this long-term experimental study was to develop and recommend appropriate manure and nutrient management practices to producers to minimize the water contamination potential and enhance the use of swine manure as inorganic fertilizer. A third component of this study was to determine the potential effects of rye as a cover crop to reduce nitrate loss to shallow ground water.

Impact of CO2 enrichment on organic matter dynamics during nutrient induced coastal phytoplankton blooms

A mesocosm experiment was conducted to investigate the impact of rising fCO2 on the build-up and decline of organic matter during coastal phytoplankton blooms. Five mesocosms (~38 m³ each) were deployed in the Baltic Sea during spring (2009) and enriched with CO2 to yield a gradient of 355-862 µatm. Mesocosms were nutrient fertilized initially to induce phytoplankton bloom development. Changes in particulate and dissolved organic matter concentrations, including dissolved high-molecular weight (>1 kDa) combined carbohydrates, dissolved free and combined amino acids as well as transparent exopolymer particles (TEP), were monitored over 21 days together with bacterial abundance, and hydrolytic extracellular enzyme activities. Overall, organic matter followed well-known bloom dynamics in all CO2 treatments alike. At high fCO2, higher dPOC:dPON during bloom rise, and higher TEP concentrations during bloom peak, suggested preferential accumulation of carbon-rich components. TEP concentration at bloom peak was significantly related to subsequent sedimentation of particulate organic matter. Bacterial abundance increased during the bloom and was highest at high fCO2. We conclude that increasing fCO2 supports production and exudation of carbon-rich components, enhancing particle aggregation and settling, but also providing substrate and attachment sites for bacteria. More labile organic carbon and higher bacterial abundance can increase rates of oxygen consumption and may intensify the already high risk of oxygen depletion in coastal seas in the future.

Land based mesocosm experiment studying the simultaneous impact of warming and acidification on the planktonic food web of the Eastern Mediterranean

A land based mesocosm experiment focusing on the study of the simultaneous impact of warming and acidification on the planktonic food web of the Eastern Mediterranean took place in August-September 2013 at the mesocosm facilities of HCMR in Crete (CRETACOSMOS). Two different pCO2 (present day and predicted for year 2100) were applied in triplicate mesocosms of 3 m**3. This was tested in two different temperatures (ambient seawater T and ambient T plus 3°C). Twelve mesocosms in total were incubated in two large concrete tanks. Temperature was controlled by sophisticated, automated systems. A large variety of chemical, biological and biochemical variables were studied, including salinity, temperature, light and alkalinity measurements, inorganic and organic, particulate and dissolved, nutrient analyses, biological stock (Chla concentration, enumeration and community composition of microbial, phyto- and zooplankton organisms) and rate (primary, bacterial, viral production, copepod egg production, zooplankton grazing, N2 fixation, P uptake) measurements, bacterial DNA extraction and phytoplankton transcriptomics, calcifiers analyses. Twenty three scientists from 6 Institutes and 5 countries participated in this experiment.

Impact of changing carbonate chemistry, temperature, and salinity on growth and test degradation of the benthic foraminifer Ammonia aomoriensis

The present study investigated the combined effects of ocean acidification, temperature, and salinity on growth and test degradation of Ammonia aomoriensis. This species is one of the dominant benthic foraminifera in near-coastal habitats of the southwestern Baltic Sea that can be particularly sensitive to changes in seawater carbonate chemistry. To assess potential responses to ocean acidification and climate change, we performed a fully crossed experiment involving three temperatures (8, 13, and 18°C), three salinities (15, 20, and 25) and four pCO2 levels (566, 1195, 2108, and 3843 µatm) for six weeks. Our results highlight a sensitive response of A. aomoriensis to undersaturated seawater with respect to calcite. The specimens continued to grow and increase their test diameter in treatments with pCO2 <1200 µatm, when Omega calc >1. Growth rates declined when pCO2 exceeded 1200 µatm (Omega calc <1). A significant reduction in test diameter and number of tests due to dissolution was observed below a critical Omega calc of 0.5. Elevated temperature (18°C) led to increased Omega calc, larger test diameter, and lower test degradation. Maximal growth was observed at 18°C. No significant relationship was observed between salinity and test growth. Lowered and undersaturated Omega calc, which results from increasing pCO2 in bottom waters, may cause a significant future decline of the population density of A. aomoriensis in its natural environment. At the same time, this effect might be partially compensated by temperature rise due to global warming.

Impact of product-related environmental regulations in Asia : descriptive statistics from a survey of firms in Penang, Malaysia

This paper summarizes the main results of a unique firm survey conducted in Penang, Malaysia in 2012 on product-related environmental regulations. The results show that firms receiving foreign-direct investment have adapted well to regulations but faced more rejections. Several research questions are addressed and examined by using the survey data. Major findings are as follows. First, adaptation involves changes in input procurement and market diversification, which potentially changes the structure of supply chains. Second, belonging to global supply chains is a key factor in compliance, but this requires firms to meet tougher customer requirements. Third, there is much room for government policy to play a role in assisting firms.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.