Understanding causal relationships between the built and social environment, health and associated behaviours and risk factors

Introduction: Built environment interventions designed to reduce non-communicable diseases and health inequity, complement urban planning agendas focused on creating more ‘liveable’, compact, pedestrian-friendly, less automobile dependent and more socially inclusive cities.However, what constitutes a ‘liveable’ community is not well defined. Moreover, there appears to be a gap between the concept and delivery of ‘liveable’ communities. The recently funded NHMRC Centre of Research Excellence (CRE) in Healthy Liveable Communities established in early 2014, has defined ‘liveability’ from a social determinants of health perspective. Using purpose-designed multilevel longitudinal data sets, it addresses five themes that address key evidence-base gaps for building healthy and liveable communities. The CRE in Healthy Liveable Communities seeks to generate and exchange new knowledge about: 1) measurement of policy-relevant built environment features associated with leading non-communicable disease risk factors (physical activity, obesity) and health outcomes (cardiovascular disease, diabetes) and mental health; 2) causal relationships and thresholds for built environment interventions using data from longitudinal studies and natural experiments; 3) thresholds for built environment interventions; 4) economic benefits of built environment interventions designed to influence health and wellbeing outcomes; and 5) factors, tools, and interventions that facilitate the translation of research into policy and practice. This evidence is critical to inform future policy and practice in health, land use, and transport planning. Moreover, to ensure policy-relevance and facilitate research translation, the CRE in Healthy Liveable Communities builds upon ongoing, and has established new, multi-sector collaborations with national and state policy-makers and practitioners. The symposium will commence with a brief introduction to embed the research within an Australian health and urban planning context, as well as providing an overall outline of the CRE in Healthy Liveable Communities, its structure and team. Next, an overview of the five research themes will be presented. Following these presentations, the Discussant will consider the implications of the research and opportunities for translation and knowledge exchange. Theme 2 will establish whether and to what extent the neighbourhood environment (built and social) is causally related to physical and mental health and associated behaviours and risk factors. In particular, research conducted as part of this theme will use data from large-scale, longitudinal-multilevel studies (HABITAT, RESIDE, AusDiab) to examine relationships that meet causality criteria via statistical methods such as longitudinal mixed-effect and fixed-effect models, multilevel and structural equation models; analyse data on residential preferences to investigate confounding due to neighbourhood self-selection and to use measurement and analysis tools such as propensity score matching and ‘within-person’ change modelling to address confounding; analyse data about individual-level factors that might confound, mediate or modify relationships between the neighbourhood environment and health and well-being (e.g., psychosocial factors, knowledge, perceptions, attitudes, functional status), and; analyse data on both objective neighbourhood characteristics and residents’ perceptions of these objective features to more accurately assess the relative contribution of objective and perceptual factors to outcomes such as health and well-being, physical activity, active transport, obesity, and sedentary behaviour. At the completion of the Theme 2, we will have demonstrated and applied statistical methods appropriate for determining causality and generated evidence about causal relationships between the neighbourhood environment, health, and related outcomes. This will provide planners and policy makers with a more robust (valid and reliable) basis on which to design healthy communities.

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.

The use of amenities in high density neighbourhoods by older urban Australians residents

Like other major cities, Brisbane (Australia) has adopted policies to increase residential densities to meet the liveability goal of decreasing car dependence. This objective hinges on urban neighbourhoods being amenity-rich spaces, reducing the need for residents to leave their neighbourhood for everyday living. While older people are attracted to urban settings, there has been little empirical evidence linking liveability satisfaction with older people's use of urban neighbourhoods. Using a case study approach employing qualitative (diaries, in-depth interviews) and quantitative (Global Positioning Systems and Geographical Information Systems mapping) methods,this paper explores the effect of the neighbourhood environment and its influence on liveability for older urban people. Reliance on motor vehicles and issues with availability and access to local amenities inhibit local participation for older people. Highlighting these issues furthers our understanding of the landscape planning and design factors that make urban neighbourhoods more liveable for older residents.

The Well London program - a cluster randomized trial of community engagement for improving health behaviors and mental wellbeing: baseline survey results

Background The Well London programme used community engagement, complemented by changes to the physical and social neighbourhood environment, to improve physical activity levels, healthy eating and mental wellbeing in the most deprived communities in London. The effectiveness of Well London is being evaluated in a pair-matched cluster randomised trial (CRT). The baseline survey data are reported here. Methods The CRT involved 20 matched pairs of intervention and control communities (defined as UK census lower super output areas; ranked in the 11% most deprived LSOAs in London by Index of Multiple Deprivation) across 20 London boroughs. The primary trial outcomes, sociodemographic information and environmental neighbourhood characteristics were assessed in three quantitative components within the Well London CRT at baseline: a cross-sectional, interviewer-administered adult household survey; a self-completed, school-based adolescent questionnaire; a fieldworker completed neighbourhood environmental audit. Baseline data collection occurred in 2008. Physical activity, healthy eating and mental wellbeing were assessed using standardised, validated questionnaire tools. Multiple imputation was used to account for missing data in the outcomes and other variables in the adult and adolescent surveys. Results There were 4107 adults and 1214 adolescent respondents in the baseline surveys. The intervention and control areas were broadly comparable with respect to the primary outcomes and key sociodemographic characteristics. The environmental characteristics of the intervention and control neighbourhoods were broadly similar. There was greater between cluster variation in the primary outcomes in the adult population compared to the adolescent population. Levels of healthy eating, smoking and self-reported anxiety/depression were similar in the Well London population and the national Health Survey for England. Levels of physical activity were higher in the Well London population but this is likely to be due to the different measurement tools used in the two surveys. Conclusions Randomisation of social interventions such as Well London is acceptable and feasible and in this study the intervention and control arms are well balanced with respect to the primary outcomes and key sociodemographic characteristics. The matched design has improved the statistical efficiency of the study amongst adults but less so amongst adolescents. Follow-up data collection will be completed 2012.

How does socio economic position link to health behaviour? Sociological pathways and perspectives for health promotion

Socio economic inequalities in adult health behaviour are consistently observed. Despite a well-documented pattern, social determinants of variations in health behaviour have not been sufficiently clarified. This article therefore presents sociological pathways to explain the existing inequalities in health behaviour. At a micro level, control beliefs have been part of several behavioural theories. We suggest that these beliefs might bridge the gap between sociology and psychology by emphasising their roots in fundamental socio-economic environments. At a meso level, social networks and support have not been explicitly considered as behavioural determinants. This contribution states that these social factors influence health behaviour while being unequally distributed across society. At a macro level, characteristics of the neighbourhood environment influence health behaviour of its residents above and beyond their individual background. Providing further opportunity for policy makers, it is shown that peer and school context equalise inequalities in risky behaviour in adolescence. As a conclusion, factors such as control expectations, social networks, neighbourhood characteristics, and school context should be included as strategies to improve health behaviour in socially disadvantaged people.

Promoción de salud para la generación de entornos saludables en un barrio vulnerable: el caso de Las Remudas, Gran Canaria

Las desigualdades sociales en salud se reflejan también en la segregación espacial de barrios que concentran desventajas estructurales generando entornos poco saludables. Este estudio describe las acciones y estrategias desarrolladas, dentro de un proceso de intervención socio-comunitaria en salud, para mejorar el entorno de un barrio desfavorecido y la percepción vecinal de las transformaciones vividas. Metodología: Se construye un estudio de caso a partir de entrevistas semiestructuradas a informantes clave. Resultado: los informantes reconocen la transformación del entorno en aspectos urbanísticos, ambientales y sociales y la importancia de su participación en ello. La apertura de nuevos comercios o la disminución de la criminalidad son indicadores objetivos de esta mejora. Conclusión: Las intervenciones de promoción de salud para mejorar el entorno deben considerar su multidimensionalidad y, por tanto, su abordaje multisectorial a través de metodologías participativas que involucren a los diversos actores sociales.

Residents' perceptions of walkability attributes in objectively different neighbourhoods: a pilot study

Physical attributes of local environments may influence walking. We used a modified version of the Neighbourhood Environment Walkability Scale to compare residents' perceptions of the attributes of two neighbourhoods that differed on measures derived from Geographic Information System databases. Residents of the high-walkable neighbourhood rated relevant attributes of residential density, land-use mix (access and diversity) and street connectivity, consistently higher than did residents of the low-walkable neighbourhood. Traffic safety and safety from crime attributes did not differ. Perceived neighbourhood environment characteristics had moderate to high test retest reliabilities. Neighbourhood environment attribute ratings may be used in population surveys and other studies. (c) 2004 Elsevier Ltd. All rights reserved.

Prospective study of individual, social, and environmental predictors of physical activity: women's leisure running

Background: Understanding and influencing the determinants of physical activity is an important public health challenge. We used prospective data to examine the influence of individual, social, and environmental factors on physical activity behaviour, using regular running as the behavioural model. Methods: Over 500 middle-aged women completed two consecutive questionnaires in 2000 and 2002. Logistic regression analyses were used to examine factors predicting adoption of and regression from regular leisure-time running during the follow-up. Results: Women who frequently used behavioural change skills were more likely to adopt regular running (OR=4.0, CI=1.7-9.5). There was an interaction between the enjoyment of running and family support: those who rated enjoyment of running high and reported high family support were less likely to adopt running (OR= 0.2, CI = 0.1-0.5). Women who reported infrequent use of motives were more likely (OR = 3.3, CI = 1.6-6.9) to regress from regular running. There was an interaction between perceived health and the neighbourhood environment: those who perceived themselves to be in poor health and had an unattractive neighbourhood were more likely (OR = 2.7, CI = 0.9-8.3) to regress from regular running. Conclusions: Behavioural skills and enjoyment may be of particular importance for the adoption of regular activity; social support and an aesthetically attractive neighbourhood are likely to have a key role in encouraging maintenance. (c) 2004 Elsevier Ltd. All rights reserved.

Factores asociados al desplazamiento activo en bicicleta al colegio en el Distrito Bogotá, Colombia. Estudio FUPRECOL

Introducción: El transporte activo (TA) puede ser una oportunidad para incrementar los niveles de actividad física diarios de los niños y adolescentes, además de destacarse como una estrategia práctica, accesible y sostenible a largo plazo. Objetivos: El objetivo del presente estudio es doble: Analizar los patrones de desplazamiento activo en bicicleta al y desde el centro educativo, y b) Identificar los factores asociados al uso de la bicicleta como TA; en una muestra de niños y jóvenes pertenecientes a escuelas oficiales de Bogotá, Colombia. Material y métodos: Se trata de un sub-análisis del estudio FUPRECOL en 8060 niños y adolescentes entre los 9-17 años de edad). El modo de desplazamiento del escolar fue determinado a través de la pregunta: “¿Durante los últimos 7 días, usaste bicicleta para ir al colegio/escuela y volver a la casa?. Dicha respuesta se categorizó en activos “Si” (si se desplazan en bicicleta) y pasivos “No” (si se desplazan en vehículo motorizado). Se midieron parámetros antropométricos de peso, talla y perímetro de cintura. El máximo nivel de estudios alcanzados por la madre/padre (no reporta, primaria o secundaria/técnico o tecnólogo/universitario o postgrado) y la composición del hogar (vive con padre/vive con madre/con ambos padres/con abuelos/otros familiares) se auto-reportó por los padres. Las relaciones entre el TA y los factores anteriormente descritos se analizaron mediante regresión logística binaria. Resultados: El 21,9% del total de la muestra reporta usar la bicicleta como medio de transporte y el 7,9% acumula más de 120 minutos al día. Se observó una mayor probabilidad de usar la bicicleta como medio de desplazamiento activo a la escuela en los varones, en los jóvenes entre 9 y 12 años, y en aquellos cuyo padre/madre reportaron mayor grado académico, es decir, “universitario/postgrado”. 3 Conclusión: Los hallazgos del presente estudio sugieren que es necesario promover el TA desde la niñez, poniendo mayor énfasis en el paso a la adolescencia y en las jóvenes, para así aumentar los niveles diarios de AF de estos.

Topological SLAM using neighbourhood information of places

Perceptual aliasing makes topological navigation a difficult task. In this paper we present a general approach for topological SLAM~(simultaneous localisation and mapping) which does not require motion or odometry information but only a sequence of noisy measurements from visited places. We propose a particle filtering technique for topological SLAM which relies on a method for disambiguating places which appear indistinguishable using neighbourhood information extracted from the sequence of observations. The algorithm aims to induce a small topological map which is consistent with the observations and simultaneously estimate the location of the robot. The proposed approach is evaluated using a data set of sonar measurements from an indoor environment which contains several similar places. It is demonstrated that our approach is capable of dealing with severe ambiguities and, and that it infers a small map in terms of vertices which is consistent with the sequence of observations.

Indoor environment sustainability of residential industrial housing in Malaysia

The importance of sustainable development has been internationally recognized and the principles have been widely used as an impetus for promoting housing sustainability. In the situation of mixed-use urban development in close proximity to heavy industrial areas in Malaysia, rising incomes are developing hand in hand with higher expectations for better and more sustainable housing designs. Negative environmental impacts due current deficiency in Malaysia’s approach to the implementation of sustainable development principles can be seen in this case study of the Pasir Gudang Industrial Area in Malaysia. This study aimed to highlight the level of residents’ satisfaction with living near the industrial area, and to relate their awareness of the relevance of sustainable principles with indoor environmental conditions, which found that the residents’ has limited understanding of the environmental problems in their indoor living conditions and in their neighborhoods. This study has suggested that proactive and integrated involvement by housing authorities from all levels of government in Malaysia should be encouraged in order to rationalise the approaches to develop better planning solutions for such mixed-used urban developments. This initiative should then encourage housing vendors to provide innovative ‘smart’ technological changes to their projects and so, to achieve a new direction in sustainable housing development.