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Objectives: To estimate the overall health impact of transferring commuting trips from car to bicycle.. Design and setting: In this study registry information on location of home and work for residents in the County of Stockholm was used to obtain the shortest travel route on a network of bicycle paths and roads. Current modes of travel to work were based on travel survey data. The relation between duration of cycling and distance cycled was established as a basis for selecting the number of individuals that normally would drive a car to their work place, but have a distance to work that they could bicycle within 30 minutes. The change in traffic flows was estimated by a transport model (LuTrans) and effects on road traffic injuries and fatalities were estimated by using national hospital injury data. Effects on air pollution concentrations were modelled using dispersion models. Results: Within the scenario, 111 000 commuters would shift from car to bicycle. This corresponds to 32% of the existing car commuters. On average the increased physical activity reduced the one-year mortality risk by 12% among the additional bicyclists corresponding to 16 fewer premature deaths per year. Including the number of years lost due to morbidity, the total number of disability adjusted life years (DALYs) gained was 696. The amount of DALYs per year gained in the general population due to reduced air pollution concentrations at home addresses was 471. The number of DALYs lost by traffic injuries was 176. Including also air pollution effects among bicyclists, the scenario was calculated to each year give a net benefit of 939 DALYs. Conclusion: The health impact assessment of transferring commuting by car to bicycle estimated large health benefits even then considering injuries and air pollution exposure among bicyclists., FAAP

Trafikverket behöver bättre metoder för att beskriva och värdera hälsoeffekter av en förändrad luftföroreningsexponering från vägtrafik. I detta finns ett kontinuerligt behov av att uppdatera och förbättra kunskapsunderlaget och metodiken för att beräkna och värdera hälsoeffekter. En viktig del i arbetet är att samordna forskningsresultat och beräkningsunderlag för att harmonisera olika tillämpningar där hälsoeffekter beskrivs. I den här rapporten presenteras resultat från ett forskningsprojekt som bidrar med beräkningar av fler hälsoeffekter och en ökad harmonisering. Umeå universitet (huvudansvarig) och Miljöförvaltningen i Stockholms stad har genomfört projektet med finansiering från Trafikverket. De slutsatser och rekommendationer som uttrycks i rapporten är författarnas egna och speglar inte nödvändigtvis Trafikverkets uppfattning.

In most societies, resources and opportunities are concentrated in neighbor-hoods and workplaces occupied by the host population. The spatial assimilationand place stratification theories propose trajectories (the sequences of events)leading to minority and migrant access to or exclusion from these advantageousplaces. However, most previous research on these theories did not ask whethersuch theorized trajectories occur. We apply sequence analysis to decade-long res-idence and workplace histories of newly arrived migrants in Sweden to identify atypology of combined residence-work trajectories. The seven types of trajecto-ries in our typology are characterized by varying degrees of proximity to thehost population in residential neighborhoods and workplaces and by different pat-terns of change in such proximity over time. The pivotal role of socioeconomicgains in spatial assimilation, posited by the namesake theory, is not supported, aswe do not find that migrant employment precedes residence alongside the hostpopulation. The importance of housing-market discrimination for migrants’exclusion from host-dominated spaces, posited by place stratification theory, isonly weakly supported, as we find that migrants from less affluent countries accu-mulate disadvantage over time, likely due to discrimination in both the labor andhousing markets. Our findings also underscore the need for new theories explain-ing migrant residential outcomes which apply to contexts where migrant-denseneighborhoods are still forming.

Objectives: The study aims to make use of individual data to estimate the impact on premature mortality due to both existing commuter bicycling and the potential impact due to increased physical activity through shifting transport mode from car commuting to bicycling. Methods: Using registry data on home and work addresses for the population of Stockholm County the shortest bicycling route on a network of bicycle paths and roads was retrieved. Travel survey data were used to establish current modes of commuting. The relation between duration of bicycling and distance bicycled within the general population in 2015 was established as a basis for identifying individuals that currently drive a car to work but were estimated to have the physical capacity to bicycle to work within 30 min. Within this mode-shift scenario from car-to-bike the duration of bicycling per week was estimated, both among current and potential bicycle commuters. The health impact assessment (HIA) on mortality due to bicycle commuting physical activity was estimated using the same relative risk as within the WHO Health Economic Assessment Tool. Results: The current number of bicycle commuters were 53 000, and the scenario estimated an additional 111 000. Their mean bicycle distances were 4.5 and 3.4 km, respectively. On average these respective amounts of physical activity reduced the yearly mortality by 16% and 12%, resulting in 11.3 and 16.2 fewer preterm deaths per year. Conclusion: The HIA of transferring commuting by car to bicycle estimated large health benefits due to increased physical activity., FAAP

There has been a strong degree of interest over the last 30 years towards immigrant segregation in Europe. This paper aims to contribute towards the existing body of research by extending the multi-scalar analysis of patterns of immigrant residential segregation into a coherent international comparative study of cities of different sizes. We investigate the patterns of immigrant-native segregation at different geographical scales, along with their correlates, in more than a hundred cities in 2011 across Germany, Spain, Sweden, the Netherlands, and the United Kingdom. Our findings suggest that cities in the UK are the most highly segregated in Europe. The positions of the other countries in the ‘European segregation ranking’ depend upon the considered immigrant group and spatial scale. The national context is consistently the most important factor in understanding segregation at multiple spatial scales. However, even while taking into account the national contexts, the structural-ecological factors remain important predictors of segregation patterns in Europe.

This study aims to use dispersion-modeled concentrations of nitrogen oxides (NOx) and black carbon (BC) to estimate bicyclist exposures along a network of roads and bicycle paths. Such modeling was also performed in a scenario with increased bicycling. Accumulated concentrations between home and work were thereafter calculated for both bicyclists and drivers of cars. A transport model was used to estimate traffic volumes and current commuting preferences in Stockholm County. The study used individuals' home and work addresses, their age, sex, and an empirical model estimate of their expected physical capacity in order to establish realistic bicycle travel distances. If car commuters with estimated physical capacity to bicycle to their workplace within 30 min changed their mode of transport to bicycle, >110,000 additional bicyclists would be achieved. Time-weighted mean concentrations along paths were, among current bicyclists, reduced from 25.8 to 24.2 mu g/m(3) for NOx and 1.14 to 1.08 mu g/m(3) for BC. Among the additional bicyclists, the yearly mean NOx dose from commuting increased from 0.08 to 1.03 mu g/m(3). This would be expected to yearly cause 0.10 fewer deaths for current bicycling levels and 1.7 more deaths for additional bicycling. This increased air pollution impact is much smaller than the decrease in the total population.

One main goal of sustainability is climate action, which is determined by the United Nations as one that encourages climate resilience and mitigating emissions. Sweden is a leading country to follow this global agenda with major efforts on decarbonization and adaptation. For these purposes, however, detailed analyses are required to assess the trajectories by and the impacts on various sectors. Regarding tourism, which is a main sector of the Swedish economy that significantly fosters regional development, not much scientific foundation has been laid so far. This is especially true for the highly climate-dependent ski tourism sub-sector, albeit Sweden is among the top players of the global ski market, following a growth trend unlike many other conventional destinations. This study aims for a detailed assessment on the vulnerability of Swedish ski tourism to climate change and its implications and consequences for resilience building and mitigation efforts by pursuing an interdisciplinary methodology that employs and combines discrete choice experiment, geographical information systems, agent-based modelling and the newly proposed Ski Climate Index. The specific research questions are; (1) “how exposed are the existing and the potential ski areas in Sweden to climate change?”, (2) “how sensitive and adaptive is the Swedish ski tourism market to climate change?”, and (3) “what are the potential risks of increased emissions due to adaptation efforts of the Swedish ski tourism sector as well as any counterproductivity associated with further introduction of mitigation policies, and what measures could be taken to avoid any increase in such ‘rebound’ effects?”. In this respect, the results are expected to provide the stakeholders with a thorough agenda for adaptation that takes account of its interrelationship with mitigation and to contribute to literature with the interdisciplinary methodology and the geographical scope. Implications for the Nordic and the global scale

This study aims to develop a typology of generic meeting places based on social contact and mixing of relevance for infectious disease transmission. Data was collected by means of a contact diary survey conducted on a representative sample of the Swedish population. The typology is derived from a cluster analysis accounting for four dimensions associated with transmission risk: visit propensity and its characteristics in terms of duration, number of other persons present and likelihood of physical contact. In the analysis, we also study demographic, socioeconomic and geographical differences in the propensity of visiting meeting places. The typology identifies the family venue, the fixed activity site, the family vehicle, the trading plaza and the social network hub as generic meeting places. The meeting place typology represents a spatially explicit account of social contact and mixing relevant to infectious disease modelling where the social context of the outbreak can be highlighted in light of the actual infectious disease.

OBJECTIVE: To investigate associations between exposure to air pollution and child and adolescent mental health. DESIGN: Observational study. SETTING: Swedish National Register data on dispensed medications for a broad range of psychiatric disorders, including sedative medications, sleeping pills and antipsychotic medications, together with socioeconomic and demographic data and a national land use regression model for air pollution concentrations for NO2, PM10 and PM2.5. PARTICIPANTS: The entire population under 18 years of age in 4 major counties. We excluded cohort members whose parents had dispensed a medication in the same medication group since the start date of the register. The cohort size was 552 221. MAIN OUTCOME MEASURES: Cox proportional hazards models to estimate HRs and their 95% CIs for the outcomes, adjusted for individual-level and group-level characteristics. RESULTS: The average length of follow-up was 3.5 years, with an average number of events per 1000 cohort members of ∼21. The mean annual level of NO2 was 9.8 µg/m(3). Children and adolescents living in areas with higher air pollution concentrations were more likely to have a dispensed medication for a psychiatric disorder during follow-up (HR=1.09, 95% CI 1.06 to 1.12, associated with a 10 µg/m(3) increase in NO2). The association with NO2 was clearly present in 3 out of 4 counties in the study area; however, no statistically significant heterogeneity was detected. CONCLUSION: There may be a link between exposure to air pollution and dispensed medications for certain psychiatric disorders in children and adolescents even at the relatively low levels of air pollution in the study regions. The findings should be corroborated by others.

Contemporary cities are becoming more and more diverse in population as a result of immigration. Research shows that while residential neighborhoods are becoming ethnically more diverse within cities, residential segregation from natives has overall remained persistently high. High levels of segregation are often seen as negative, preventing the integration of immigrants into their host society and having a negative impact on people's lives. Where as most studies of segregation deal with residential neighborhoods, this paper investigates segregation at workplaces for newly arrived immigrant men and women from the Global South to Sweden. By using the domain approach, we focus on the relationship between workplace segregation, residential segregation, and the ethnic composition of households. Using longitudinal register data from Sweden, we find that residential segregation is much weaker related to workplace segregation than revealed by studies using cross-sectional data. Furthermore, the residential context is not an important factor in explaining workplace segregation for immigrant men. The most important factors shaping workplace segregation pertain to economic sector and city size.

Workplaces are one of the most important regular meeting places in society. The aim of this study was to use simulation experiments to examine the impact of different workplace cultures on influenza dissemination during pandemics. The impact is investigated by experiments with defined social-mixing patterns at workplaces using semi-virtual models based on authentic sociodemographic and geographical data from a North European community (population 136 000). A simulated pandemic outbreak was found to affect 33% of the total population in the community with the reference academic-creative workplace culture; virus transmission at the workplace accounted for 10·6% of the cases. A model with a prevailing industrial-administrative workplace culture generated 11% lower incidence than the reference model, while the model with a self-employed workplace culture (also corresponding to a hypothetical scenario with all workplaces closed) produced 20% fewer cases. The model representing an academic-creative workplace culture with restricted workplace interaction generated 12% lower cumulative incidence compared to the reference model. The results display important theoretical associations between workplace social-mixing cultures and community-level incidence rates during influenza pandemics. Social interaction patterns at workplaces should be taken into consideration when analysing virus transmission patterns during influenza pandemics.

Pandemic simulation is a useful tool for analyzing outbreaks and exploring the impact of variations in disease, population, and intervention models. Unfortunately, this type of simulation can be quite time-consuming especially for large models and significant outbreaks, which makes it difficult to run the simulations interactively and to use simulation for decision support during ongoing outbreaks. Improved run-time performance enables new applications of pandemic simulations, and can potentially allow decision makers to explore different scenarios and intervention effects. Parallelization of infection-probability calculations and multicore architectures can take advantage of modern processors to achieve significant run-time performance improvements. However, because of the varying computational load during each simulation run, which originates from the changing number of infectious persons during the outbreak, it is not useful to us the same multicore setup during the simulation run. The best performance can be achieved by dynamically changing the use of the available processor cores to balance the overhead of multithreading with the performance gains of parallelization.

Immigrant–native segregation is present in the spaces in which individuals from different ethnic/racial groups practice their everyday lives; interact with others and develop their ethnic, social and spatial networks. The overwhelming majority of academic research on immigrant segregation has focused on the residential domain, thus largely overlooking other arenas of daily interaction. The present study contributes to the emerging literature on immigrant residential and workplace segregation by examining changes in patterns of residential and workplace segregation over time. We draw our data from the Stockholm metropolitan region, Sweden’s main port of entry for immigrants. The results suggest a close association between residential and workplace segregation. Immigrant groups that are more segregated at home are also more segregated in workplace neighborhoods. More importantly, we found that a changing segregation level in one domain tends to involve a similar trend in the other domain.

Simulation is an important resource for studying the dynamics of pandemic influenza and predicting the potential impact of interventions. However, there are several challenges for the design of such simulator architectures. Specifically, it is difficult to develop simulators that combine flexibility with run-time performance. This tradeoff is problematic in the pandemic-response setting because it makes it challenging to extend and adapt simulators for ongoing situations where rapid results are indispensable. Simulation architectures based on aspect-oriented programming can model specific concerns of the simulator and can allow developers to rapidly extend the simulator in new ways without sacrificing run-time performance. It is possible to use such aspects in conjunction with separate simulation models, which define community, disease, and intervention properties. The implication of this research for pandemic response is that aspects can add a novel layer of flexibility to simulation environments, which enables modelers to extend the simulator run-time component to new requirements that go beyond the original modeling framework.

Aim: To investigate celiac disease (CD) clustering at different geographical levels and to examine the association between neighborhood demographic and socioeconomic conditions and the risk of neighborhood CD. Methods: We included 2080 children diagnosed with CD between 1998 and 2003, identified from 43 of the 47 reporting hospitals in Sweden. A total of 8036 small area market statistics (SAMS) areas were included; these were nested in 253 municipalities that were further nested into eight ‘nomenclature of territorial units for statistics’ (NUTS) 2 regions. We performed multilevel logistic regression analyses. Results: We found the highest geographical variation in CD incidence at the municipality level, compared to the region level. The probability of having CD increased in the statistical areas of (SAMS) areas with higher average annual work income, with an odds ratio (OR) of 2.24 and 95% CI of 1.76–2.85. Reduced CD risk in neighborhoods was associated with higher average age (OR 0.96; 95% CI 0.95–0.97), higher proportion of residents with a university education (OR 0.98; 95% CI 0.97–0.99), and higher level of industrial and commercial activity (OR 0.59; 95% CI 0.44–0.82). We found no significant association between CD risk and population density, proportion of Nordic to non-Nordic inhabitants, nor share of the population with only a compulsory education. Conclusions: Neighborhood composition influences CD risk. This is one of the first attempts to identify factors explaining geographical variation in CD.

During the 1960s in Sweden, socio-economic differentials decreased sharply at the same time as the labor force participation of married women and aggregate divorce rates increased more rapidly than during any other period of the twentieth century. The aim of this paper is to investigate how the socio-economic composition of the couple influenced the probability of divorce during this period of rapid restructuring. The study uses a large dataset covering the entire married population of Sweden in 1960 and applies a binary model whereby the couples are analyzed as units rather than separate individuals to model divorce during the period 1960-1965. The main results show that the equalization process between genders and social classes during this period contributed to the decrease in marital stability. Dual-provider families exhibit substantially higher probabilities of divorce as compared to traditional single-provider families. We also find that the socio-economic gradient of divorce had become negative by the early 1960s and that couples with low socio-economic status contributed more to the increase in divorce than did couples in the higher strata. A difference between the results reached in this study and those from divorce research covering later decades is that children do not reduce the probability of divorce when the wife's labor force participation is controlled for. The results indicate that the determinants of divorce have varied across different phases of the divorce transition during the twentieth century and that a historical perspective is necessary if we are to understand the long-term process that has produced current marital behavior.

Syndromic data sources have been sought to improve the timely detection of increased influenza transmission. This study set out to examine the prospective performance of telenursing chief complaints in predicting influenza activity. Data from two influenza seasons (2007/08 and 2008/09) were collected in a Swedish county (population 427,000) to retrospectively determine which grouping of telenursing chief complaints had the largest correlation with influenza case rates. This grouping was prospectively evaluated in the three subsequent seasons. The best performing telenursing complaint grouping in the retrospective algorithm calibration was fever (child, adult) and syncope (r=0.66; p<0.001). In the prospective evaluation, the performance of 14-day predictions was acceptable for the part of the evaluation period including the 2009 influenza pandemic (area under the curve (AUC)=0.84; positive predictive value (PPV)=0.58), while it was strong (AUC=0.89; PPV=0.93) for the remaining evaluation period including only influenza winter seasons. We recommend the use of telenursing complaints for predicting winter influenza seasons. The method requires adjustments when used during pandemics.

Ground level ozone [ozone] is considered a harmful air pollutant but there is a knowledge gap regarding its long term health effects. The main aim of this study is to develop local Land Use Regression [LUR] models that can be used to study long term health effects of ozone. The specific aim is to develop spatial LUR models for two Swedish cities, Umea and Malmo, as well as a temporal model for Malmo in order to assess ozone exposure for long term epidemiological studies. For the spatial model we measured ozone, using Ogawa passive samplers, as weekly averages at 40 sites in each study area, during three seasons. This data was then inserted in the LUR-model with data on traffic, land use, population density and altitude to develop explanatory models of ozone variation. To develop the temporal model for Malmo, hourly ozone data was aggregated into daily means for two measurement stations in Malmo and one in a rural area outside Malmo. Using regression analyses we inserted meteorological variables into different temporal models and the one that performed best for all three stations was chosen. For Malmo the LUR-model had an adjusted model R-2 of 0.40 and cross validation R-2 of 0.17. For Umea the model had an adjusted model R-2 of 0.67 and cross validation adjusted R-2 of 0.48. When restricting the model to only including measuring sites from urban areas, the Malmo model had adjusted model R-2 of 0.51 (cross validation adjusted R-2 0.33) and the Umea model had adjusted model R-2 of 0.81 (validation adjusted R-2 of 0.73). The temporal model had adjusted model R-2 0.54 and 0.61 for the two Malmo sites, the cross validation adjusted R-2 was 0.42. In conclusion, we can with moderate accuracy, at least for Umea, predict the spatial variability, and in Malmo the temporal variability in ozone variation.

Failure to incorporate the beliefs and attitudes of the public into theoretical models of preparedness has been identified as a weakness in strategies to mitigate infectious disease outbreaks. We administered a cross-sectional telephone survey to a representative sample (n = 443) of the Swedish adult population to examine whether self-reported intentions to improve personal hygiene and increase social distancing during influenza outbreaks could be explained by trust in official information, self-reported health (SF-8), sociodemographic factors, and determinants postulated in protection motivation theory, namely threat appraisal and coping appraisal. The interviewees were asked to make their appraisals for two scenarios: a) an influenza with low case fatality and mild lifestyle impact; b) severe influenza with high case fatality and serious disturbances of societal functions. Every second respondent (50.0%) reported high trust in official information about influenza. The proportion that reported intentions to take deliberate actions to improve personal hygiene during outbreaks ranged between 45–85%, while less than 25% said that they intended to increase social distancing. Multiple logistic regression models with coping appraisal as the explanatory factor most frequently contributing to the explanation of the variance in intentions showed strong discriminatory performance for staying home while not ill (mild outbreaks: Area under the curve [AUC] 0.85 (95% confidence interval 0.82;0.89), severe outbreaks AUC 0.82 (95% CI 0.77;0.85)) and acceptable performance with regard to avoiding public transportation (AUC 0.78 (0.74;0.82), AUC 0.77 (0.72;0.82)), using handwash products (AUC 0.70 (0.65;0.75), AUC 0.76 (0.71;0.80)), and frequently washing hands (AUC 0.71 (0.66;0.76), AUC 0.75 (0.71;0.80)). We conclude that coping appraisal was the explanatory factor most frequently included in statistical models explaining self-reported intentions to carry out non-pharmaceutical hea