Suchergebnisse

Sweden has since the start of the pandemic a COVID-19 mortality rate that is 4 to 10 times higher than in the other Nordic countries. Also, measured as age-standardized all-cause excess mortality in the first half of 2020 compared to previous years Sweden failed in comparison with the other Nordic countries, but only among the elderly. Sweden has large socioeconomic and ethnic inequalities in COVID-19 mortality. Geographical, ethnic, and socioeconomic inequalities in mortality can be due to differential exposure to the virus, differential immunity, and differential survival. Most of the country differences are due to differential exposure, but the socioeconomic disparities are mainly driven by differential survival due to an unequal burden of comorbidity. Sweden suffered from an unfortunate timing of tourists returning from virus hotspots in the Alps and Sweden's government response came later and was much more limited than elsewhere. The government had an explicit priority to protect the elderly in nursing and care homes but failed to do so. The staff in elderly care are less qualified and have harder working conditions in Sweden, and they lacked adequate care for the clients. Sweden has in recent years diverged from the Scandinavian welfare model by strong commercialization of primary care and elderly care.

The Scandinavian countries and their welfare policies have long been known for their ability to reduce income inequality while boosting economic growth. Recent research from OECD has indicated that the Scandinavian countries are indeed examples of a more general positive relationship between equality and growth (64). Health equity has been anexplicit political goal in Scandinavia for decades. Nevertheless, in the health domain, average improvement has not been followed by reduced inequality – at least not between socioeconomic groups. It has in other words turned out to be a challenge of translating small inequalities in wealth into small inequalities in health. Denmark, Norway and Sweden all have legislation that indifferent ways offers local governments key roles in public health. This is partly due to local governments' responsibility for many policy areas of great relevance to health and health equity. National governments have thus largely made the WHO and EU recommendation of 'Health in All Policies'a local responsibility. In his analysis for the Nordic Council of Ministers, former Swedish Minister of Health Bo Könberg identifies tackling health inequalities as one of 14 prioritised areas for future Nordic collaboration on health (94). The fact that all of the Nordic countries share this growing problem as well as a political ambition to deal with it brought the issue onto Könberg's list. The Nordic Council of Ministers also recently listed the sustainability of the Nordic welfare state model, including its health policy, as an area of Nordic collaboration (104). However, realising the principle of health (equity) in all policiesis no simple matter. The national authorities and local government federations in Denmark, Norway and Sweden have therefore initiated various activities to support local governments in this process. One has been to ask the Department of Public Health at the University of Copenhagen to undertake an explorative study on what we can learn from experiences so far in regions and municipalities in the three countries. Political, professional, and organisational issues are all relevant here. Can we identify obstacles to and means of promoting the involvement of local policymakers within education, social care, labourmarket, environment etc. in a coordinated effort to tackle health inequalities in a Scandinavian context? The present report is the result of this study. It is based on three sources: 1. Interviews with policymakers (administrators and politicians) within healthcare administrations, childhood/education, and labour market administrations from September 2014 to March 2015*. 2. Textual analysis of available policy documents from regions and municipalities. 3. Meetings with an expert group** of individuals from the three countries, who possess considerable experience of research and/or policymaking within the area. It is important to emphasise that because we have only been able to include a small number of municipalities, our results must be regarded as exploratory and not representative. The conclusions do not represent the positions of any of the involved authorities or experts but of the authors alone. The study was commissioned by: Danish Health and Medicines Authority (www.sundhedsstyrelsen.dk) Norwegian Directorate of Health (www.helsedirektoratet.no) Public Health Agency of Sweden (www.folkhalsomyndigheten.se) Local Government Denmark (www.kl.dk)Local Government Organisation of Norway (www.ks.no) Swedish Association of Local Authorities and Regions(www.skl.se)* The municipalities have been selected by the national authorities to represent those, both large and small, which have experience in developing intersectoral policies to tackle health inequalities. Denmark: Copenhagen, Ishøj, and Vordingborg Norway: Innherred Samkommune, Fredrikstad, and Kristiansand. Sweden: Botkyrka, Degerfors-Karlskoga, Malmö, Luleå, and Västra Götaland Region** Expert group: Anna Balkfors, Espen Dahl, Göran Dahlgren, Elisabeth Fosse, Lars Iversen, Bo Pettersson, Morten Hulvej Rod, Anne Smetana, and Lennart Svensson.

Background: OECD countries over the past two decades have implemented a range of labour market integration initiatives to improve the employment chances of disabled and chronically ill individuals. This article presents a systematic review and evidence synthesis on effectiveness of government interventions to influence employers' employment practices concerning disabled and chronically ill individuals in five OECD countries. A separate paper reports on interventions to influence the behaviour of employees. Methods: Electronic and grey literature searches to identify all empirical studies reporting employment effects and/or process evaluations of government policies aimed at changing the behaviour of employers conducted between 1990 and 2008 from Canada, Denmark, Norway, Sweden and the UK. Results: Few studies provided robust evaluations of the programmes or their differential effects and selection of participants into programmes may distort the findings of even controlled studies. A population-level effect of legislation to combat discrimination by employers could not be detected. Workplace adjustments had positive impacts on employment, but low uptake. Financial incentives such as wage subsidies can work if they are sufficiently generous. Involving employers in returnto- work planning can reduce subsequent sick leave and be appreciated by employees, but this policy has not been taken up with the level of intensity that is likely to make a difference. Some interventions favour the more advantaged disabled people and those closer to the labour market. Conclusions: Future evaluations need to pay more attention to differential impact of interventions, degree of take-up, nonstigmatizing implementation and wider policy context in each country.

Purpose: To identify health-, personal- and work-related factors predictive of return to work (RTW) in employees sick-listed due to common mental health problems, such as, stress, depression, burnout, and anxiety. Methods: We distributed a baseline questionnaire to employees applying for sickness absence benefits at a large Danish welfare Department (n = 721). A total of 298 employees returned the questionnaire containing information on possible predictors of RTW. We followed up all baseline responders for a maximum of one year in a national registry of social transfer payments, including sickness absence benefits. Results: At baseline, about 9% of respondents had quit their job, 10% were dismissed and the remaining 82% were still working for the same employer. The mean time to RTW, measured from the first day of absence, was 25 weeks (median = 21) and at the end of follow-up (52 weeks) 85% had returned to work. In the fitted Cox model we found that fulfilling the DSM-IV criteria for depression predicted a longer time to RTW (HR: 0.61, CI: 0.45-0.84), whereas a better self-rated health predicted a shorter time to RTW (HR: 1.18, CI: 1.03-1.34). Employees working in the municipal (HR: 0.62, CI: 0.41-0.94) and private sector (HR: 0.65, CI: 0.44-0.96) returned to work slower compared to employees working in the governmental sector. Gender, education, cohabitation, size of workplace, low-back and upper-neck pain and employment at baseline did not predict RTW. Conclusion: Our results indicate that time to RTW is determined by both health- and work-related factors.

ABSTRACT It is a fundamental requirement of governments that they allocate resources to public services among institutions or populations that are potential competitors for funding. In Brazil, a country with clear social inequalities, equitable allocation of resources in the Unified Health System (SUS) poses a particular challenge. The present study proposes an individual-level matrix model for allocating health resources in the SUS based on data from the National Health Survey (PNS) 2013. This model is founded on a matrix of the following variables: age, sex, education, employment and income and the relationships between them. A morbidity score is used to estimate weights for each category. This model provides an opportunity for managers to use objective methods to provide a clear guide for decision-making in accordance with principles laid down in Brazilian law and in a manner based on health needs and epidemiological and demographic factors, in addition to the capacity to offer services.

ABSTRACT It is a fundamental requirement of governments that they allocate resources to public services among institutions or populations that are potential competitors for funding. In Brazil, a country with clear social inequalities, equitable allocation of resources in the Unified Health System (SUS) poses a particular challenge. The present study proposes an individual-level matrix model for allocating health resources in the SUS based on data from the National Health Survey (PNS) 2013. This model is founded on a matrix of the following variables: age, sex, education, employment and income and the relationships between them. A morbidity score is used to estimate weights for each category. This model provides an opportunity for managers to use objective methods to provide a clear guide for decision-making in accordance with principles laid down in Brazilian law and in a manner based on health needs and epidemiological and demographic factors, in addition to the capacity to offer services.