Classifying and mapping the urban transition in Vietnam

The urban transition almost always involves wrenching social adjustment as small agricultural communities are forced to adjust rapidly to industrial ways of life. Large-scale in-migration of young people, usually from poor regions, creates enormous demand and expectations for community and social services. One immediate problem planners face in approaching this challenge is how to define, differentiate, and map what is rural, urban, and transitional (i.e., peri-urban). This project established an urban classification for Vietnam by using national census and remote sensing data to identify and map the smallest administrative units for which data are collected as rural, peri-urban, urban, or urban core. We used both natural and human factors in the quantitative model: income from agriculture, land under agriculture and forests, houses with modern sanitation, and the Normalized Difference Vegetation Index. Model results suggest that in 2006, 71% of Vietnam's 10,891 communes were rural, 18% peri-urban, 3% urban, and 4% urban core. Of the communes our model classified as peri-urban, 61% were classified by the Vietnamese government as rural. More than 7% of Vietnam's land area can be classified as peri-urban and approximately 13% of its population (more than 11 million people) lives in peri-urban areas. We identified and mapped three types of peri-urban places: communes in the periphery of large towns and cities; communes along highways; and communes associated with provincial administration or home to industrial, energy, or natural resources projects (e.g., mining). We validated this classification based on ground observations, analyses of multi-temporal night-time lights data, and an examination of road networks. The model provides a method for rapidly assessing the rural–urban nature of places to assist planners in identifying rural areas undergoing rapid change with accompanying needs for investments in building, sanitation, road infrastructure, and government institutions.

Time for a break: admissions to an urban emergency department after working out-a retrospective study from Switzerland.

Background. The present retrospective study was intended to investigate whether working out and other low-speed sports can provoke cardiovascular, neurological, or traumatic damage. Material and Methods. Patient data from 2007 to 2013 was collected and saved at the university department of emergency medicine in an electronic patient record database. Results. Of the 138 patients included in this study, 83.3% (n = 115) were male and 16.7% female (n = 23). Most admissions were due to musculoskeletal accidents (n = 77; 55.8%), followed by neurological incidents (n = 23; 16.7%), cardiovascular incidents (n = 19; 13.8%), soft tissue injuries (n = 3; 2.2%), and others (n = 16; 11.6%). The mean age of the allover injured people was 36.7 years. The majority of the patients (n = 113; 81.9%) were treated as outpatients; 24 (17.4%) were inpatients. Discussion. In Switzerland, this is the first study that describes emergency department admissions after workout and examines trauma and neurological and cardiovascular incidents. As specific injuries, such as brain haemorrhages, STEMIs, and epileptic seizures, were relatively frequent, it was hypothesised that workout with its physiological changes may be an actual trigger for these injuries, at least for a specific population. Conclusion. Strenuous physical activity may trigger the risk of cardiovascular, neurological, or trauma events.

Population mixing and the risk of childhood leukaemia in Switzerland: a census-based cohort study.

Childhood leukaemia (CL) may have an infectious cause and population mixing may therefore increase the risk of CL. We aimed to determine whether CL was associated with population mixing in Switzerland. We followed children aged <16 years in the Swiss National Cohort 1990-2008 and linked CL cases from the Swiss Childhood Cancer Registry to the cohort. We calculated adjusted hazard ratios (HRs) for all CL, CL at age <5 years and acute lymphoblastic leukaemia (ALL) for three measures of population mixing (population growth, in-migration and diversity of origin), stratified by degree of urbanisation. Measures of population mixing were calculated for all municipalities for the 5-year period preceding the 1990 and 2000 censuses. Analyses were based on 2,128,012 children of whom 536 developed CL. HRs comparing highest with lowest quintile of population growth were 1.11 [95 % confidence interval (CI) 0.65-1.89] in rural and 0.59 (95 % CI 0.43-0.81) in urban municipalities (interaction: p = 0.271). Results were similar for ALL and for CL at age <5 years. For level of in-migration there was evidence of a negative association with ALL. HRs comparing highest with lowest quintile were 0.60 (95 % CI 0.41-0.87) in urban and 0.61 (95 % CI 0.30-1.21) in rural settings. There was little evidence of an association with diversity of origin. This nationwide cohort study of the association between CL and population growth, in-migration and diversity of origin provides little support for the population mixing hypothesis.

Urban expansion and its impact on urban agriculture – remote sensing based change analysis of Kizinga and Mzinga Valley – Dar Es Salaam, Tanzania

Urban agriculture is a phenomenon that can be observed world-wide, particularly in cities of devel-oping countries. It is contributing significantly to food security and food safety and has sustained livelihood of the urban and peri-urban low income dwellers in developing countries for many years. Population increase due to rural-urban migration and natural, coupled with formal as well as infor-mal urbanization are competing with urban farming for available space and scarce water resources. A multitemporal multisensoral urban change analysis over the period of 25 years (1982-2007) was performed in order to measure and visualize the urban expansion along the Kizinga and Mzinga valley in the South of Dar es Salaam. Airphotos and VHR satellite data were analyzed by using a combination of a composition of anisotropic textural measures and spectral information. The study revealed that unplanned built-up area is expanding continuously and vegetation covers and agricultural lands decline at a fast rate. The validation showed that the overall classification accuracy varied depending on the database. The extracted built-up areas were used for visual in-terpretation mapping purposes and served as information source for another research project. The maps visualize an urban congestion and expansion of nearly 18% of the total analyzed area that had taken place in the Kizinga valley between 1982 and 2007. The same development can be ob-served in the less developed and more remote Mzinga valley between 1981 and 2002. Both areas underwent fast changes where land prices still tend to go up and an influx of people both from rural and urban areas continuously increase density with the consequence of increasing multiple land use interests.