The World Health Organization recommends strategies to improve urban design, public transportation, and recreation facilities to facilitate physical activity for non-communicable disease prevention for an increasingly urbanized global population. Most evidence supporting environmental associations with physical activity comes from single countries or regions with limited variation in urban form. This paper documents variation in comparable built environment features across countries from diverse regions. The International Physical Activity and the Environment Network (IPEN) study of adults aimed to measure the full range of variation in the built environment using geographic information systems (GIS) across 12 countries on 5 continents. Investigators in Australia, Belgium, Brazil, Colombia, the Czech Republic, Denmark, China, Mexico, New Zealand, Spain, the United Kingdom, and the United States followed a common research protocol to develop internationally comparable measures. Using detailed instructions, GIS-based measures included features such as walkability (i.e., residential density, street connectivity, mix of land uses), and access to public transit, parks, and private recreation facilities around each participant’s residential address using 1-km and 500-m street network buffers. Eleven of 12 countries and 15 cities had objective GIS data on built environment features. We observed a 38-fold difference in median residential densities, a 5-fold difference in median intersection densities and an 18-fold difference in median park densities. Hong Kong had the highest and North Shore, New Zealand had the lowest median walkability index values, representing a difference of 9 standard deviations in GIS-measured walkability. Results show that comparable measures can be created across a range of cultural settings revealing profound global differences in urban form relevant to physical activity. These measures allow cities to be ranked more precisely than previously possible. The highly variable measures of urban form will be used to explain individuals’ physical activity, sedentary behaviors, body mass index, and other health outcomes on an international basis. Present measures provide the ability to estimate dose–response relationships from projected changes to the built environment that would otherwise be impossible.

We applied cartographic and geostatistical methods in analyzing the patterns of disease spread during the 2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong using geographic information system (GIS) technology. We analyzed an integrated database that contained clinical and personal details on all 1,755 patients confirmed to have SARS from 15 February to 22 June 2003. Elementary mapping of disease occurrences in space and time simultaneously revealed the geographic extent of spread throughout the territory. Statistical surfaces created by the kernel method confirmed that SARS cases were highly clustered and identified distinct disease “hot spots.” Contextual analysis of mean and standard deviation of different density classes indicated that the period from day 1 (18 February) through day 16 (6 March) was the prodrome of the epidemic, whereas days 86 (15 May) to 106 (4 June) marked the declining phase of the outbreak. Origin-and-destination plots showed the directional bias and radius of sp...

Aim To examine weather effects on the daily demand for ambulance services in Hong Kong. Methods Over 6 million cases of emergency attendance from May 2006 through April 2009 (3 years) were obtained from the Hospital Authority in Hong Kong. These cases were further stratified by age, triage levels, hospital admission status, comprehensive social security assistance (CSSA) recipients and gender. The stratification was used to correlate against weather factors to assess the dependency of these variables and their effects on the daily number of ambulance calls. Adjusted-R² values obtained from the regression analysis were used as a measure for evaluating predictability. Results The adjusted-R² of emergency cases by age groups showed proportional correlation with weather factors, which was more significant in older patients (0.76, p<0.01) than young patients (0.10, p<0.05). Furthermore, patients with more severe conditions were shown to have a higher adjusted-R² (0.63, p<0.05 for critical as opposed to 0 for non-urgent patients). Weather effects were also found more significant in women (0.50, p<0.01) and CSSA recipients (0.54, p<0.01) when compared against their corresponding reference groups (respectively men at 0.46, p<0.01 and non-CSSA recipients at 0.45, p<0.01). Moreover, average temperature appeared to be a major weather effect. Conclusions The presence of strong weather effects among different target groups indicates possibility for the development of a short-term forecast system of daily ambulance demand using weather variables. The availability of such a forecast system would render more effective deployment of the ambulance services to meet the unexpected increase in service demands.