Ogilvie et al. BMC Public Health 2010, 10:703 http://www.biomedcentral.com/1471-2458/10/703 consistency checks and data cleaning algorithms and software already developed for these instruments. Acti- graph, Actiheart and GPS data will also be merged and imported into a geographical information system (GIS). Network distances will be computed from the centroid of the unit postcode for each participant’s home address to their nearest bus stop, their nearest bus stop on the guided busway, and their workplace. GPS time and posi- tional data will be used to identify journey start and fin- ish times, estimate velocities and predict the travel mode(s) used on journeys using a published protocol [63], validated against the heart rate data obtained using Actiheart, and used to estimate the proportion of PAEE attributable to commuting. Adjacent GPS data points will be joined so that routes are depicted as linear fea- tures whose surroundings can be characterised using a range of indicators such as predominant land use type and ‘greenness’ based on detailed land use maps and an enhanced transport network layer using a protocol developed previously [64]. The main cross-sectional analyses will consist of mul- tivariate regression analyses of the demographic, socioe- conomic, geographical, psychosocial and health-related correlates of travel mode choice and physical activity and a comparison of how the findings of that analysis differ according to which summary measures of the behaviours are used. The main longitudinal quantitative analyses will consist of multivariate regression analyses to examine the effect of access to the busway and other new transport infrastructure on changes in travel beha- viour after adjustment for demographic, socioeconomic, geographical, psychosocial and health-related correlates of travel behaviour at baseline; to examine how the effect of exposure to environmental modification varies according to demographic, socioeconomic and geogra- phical characteristics and baseline level of physical activ- ity; and to examine the relationships between changes in travel behaviour and changes in overall physical activity, body mass index, wellbeing and sickness absence. Household travel diary data will be examined to explore relationships between the travel modes of household members using multivariate regression analysis. Estimation of carbon emissions Baseline carbon footprints (kg or tonnes CO2/person/ day) will be calculated from survey data based on the dis- tance, frequency, and urban or rural character of com- muting journeys computed using the GIS along with data on travel mode choice, car fuel type and engine size. They will then be recalculated from follow-up survey data to quantify the overall impact of the intervention on carbon emissions attributable to travel. Household travel diary data will also be used to examine in more detail the wider knock-on effects on carbon emissions attributable to travel by other household members. Page 10 of 13 Criterion validation of alternative methods of ascertaining active travel A small group of participants will complete synchronous core questionnaires, household travel diaries and enhanced objective measurement during follow-up data collection. Data from this overlap group will be used to validate the estimates of active travel obtained using questionnaires, travel diaries and accelerometers against the criterion of active travel ascertained from combined heart rate and movement sensor and GPS data. The purpose will be to inform the optimal choice of measurement instruments for future studies of this kind, which necessarily involves a trade-off between the valid- ity, feasibility, acceptability and cost of the various instruments available ranging from questionnaires (rela- tively cheap and acceptable to participants, but of uncer- tain validity) to combined heart rate and movement sensors (relatively expensive and somewhat less conveni- ent for participants). Qualitative analysis The analysis of the qualitative data will follow an induc- tive approach in order to arrive at a general, multi- layered ethnographic account. Content analysis of interview transcripts (first checked against the audio recordings) and photographs (stored digitally) will be conducted by a subset of the research team to ensure reliability. By identifying thematic perceptions, experi- ences and practices of travel, resulting hypotheses con- cerning the interactions with the social worlds in which they take place will be tested by re-examining the entire qualitative dataset. Guided by social theory, the analysis will be extended beyond what is merely said and shown to address why travel, journeys and places are repre- sented by participants in the way they are and how are these are embedded in larger societal contexts [65]. Discussion Few studies have set out to test the hypothesis that infrastructural improvements primarily concerned with public transport may directly or indirectly promote active travel, or to estimate the magnitude of changes in overall physical activity or other health-related impacts that may be attributable to interventions of this kind. Addressing the unresolved research and policy questions in this area is not straightforward, and the experience of designing and initiating this study illustrates several of the challenges facing researchers working on similar problems in applied public health research. One challenge is that of effectively combining different disciplinary perspectives on the research problems. This study involves a collaboration between health, environ- mental and transport researchers, a combination of quantitative and qualitative approaches to gathering and analysing data, and the examination of a range of