Background: General practice systems in the Nordic countries share certain common features. The sector is based on the Nordic model of a tax-financed supply of services with a political objective of equal access for all. The countries also share the challenges of increased political expectations to deliver primary prevention and increased workload as patients from hospital care are discharged earlier. However, within this common framework, primary care is organized differently. This is particularly in relation to the private-public mix, remuneration systems and the use of financial and non-financial incentives. Objective: The objective of this paper is to compare the differences and similarities in primary care among the Nordic countries, to create a mapping of the future plans and reforms linked to remuneration and incentives schemes, and to discuss the pros and cons for these plans with reference to the literature. An additional objective is to identify gaps in the literature and future research opportunities. Results/Conclusions: Despite the many similarities within the Nordic health care systems, the primary care sectors function under highly different arrangements. Most important are the differences in the gate-keeping function, private versus salaried practices, possibilities for corporate ownership, skill-mix and the organisational structure. Current reforms and political agendas appear to focus on the side effects of the individual countries’ specific systems. For example, countries with salaried systems with geographical responsibility are introducing incentives for private practice and more choices for patients. Countries with systems largely based on private practice are introducing more monitoring and public regulation to control budgets. We also see that new governments tends to bring different views on the future organisation of primary care, which provide considerable political tension but few actual changes. Interestingly, Sweden appears to be the most innovative in relation to introducing new incentive schemes, perhaps because decisions are made at a more decentralised level.Published: April 2016.

Highlights The decision to own your home can affect your health and well-being. Little is known about this causal relationship or possible explanations. We provide evidence at area and individual level that home ownership is goods for health. Possible explanations are better labour market outcomes and healthier lifestyles.

The Nordic countries are well-known for their welfare states. A very important feature of the welfare state is that it aims at easy and equal access to adequate health care for the entire population. For many years, the Nordic systems were automatically viewed as very similar, and they were placed in the same group when the OECD classified health care systems around the world. However, close inspection soon reveals that there are important differences between the health care systems of Denmark, Finland, Iceland, Norway and Sweden. Consequently, it is perhaps no surprise that the Nordic countries fell into three different categories when the OECD revised its classification a few years ago. In this paper, we revisit this issue and argue that the most important similarity across the Nordic countries is the institutional context in which the health care sector is embedded. Nordic health care exists in a high-trust, high-taxation setting of small open economies. With this background, we find a set of important similarities in the manner in which health care is organized and financed in the Nordic countries. To evaluate the performance of the Nordic health care system, we compare a few health quality indicators in the Nordic countries with those of five non-Nordic similarly small open European economies with the same level of income. Overall, the Nordic countries seem to be performing relatively well. Whether they will continue to do so will depend to a large extent on whether the welfare state will continue to reform itself as it has in the past.Published: April 2016.

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Background The NHS Diabetes Prevention Programme for England, “Healthier You”, encourages behaviour change regarding healthy eating and physical exercise among people identified to be at high risk of developing type 2 diabetes. The aim of this research was to examine change, and factors associated with change, in measures of HbA1c and weight in participants and completers of the programme between 2016 and 2019. Methods Participant-level data collected by programme service providers on referrals prior to March 2018 was analysed. Changes from baseline to both 6 months and completion in HbA1c and weight were examined using mixed effects linear regression, adjusting for patient characteristics, service provider and site. Results Completers had average improvements in HbA1c of 2.1 mmol/mol [95% CI: − 2.2, − 2.0] (0.19% [95% CI: − 0.20, − 0.18]) and reductions of 3.6 kg [95% CI: − 3.6, − 3.5] in weight, in absolute terms. Variation across the four providers was observed at both time points: two providers had significantly smaller average reductions in HbA1c and one provider had a significantly smaller average reduction in weight compared to the other providers. At both time points, ex- or current smokers had smaller reductions in HbA1c than non-smokers and those from minority ethnic groups lost less weight than White participants. For both outcomes, associations with other factors were small or null and variation across sites remained after adjustment for provider and case mix. Conclusions Participants who completed the programme, on average, experienced improvements in weight and HbA1c. There was substantial variation in HbA1c change and smaller variation in weight loss between providers and across different sites. Aside from an association between HbA1c change and smoking, and between weight loss and ethnicity, results were broadly similar regardless of patient characteristics.

Introduction: The Short Form Survey 12-item (SF12) mental and physical health version has been applied in several studies on populations from Sub-Saharan Africa. However, the SF12 has not been computed and validated for these populations. We address in this paper these gaps in the literature and use a health intervention example in Malawi to show the importance of our analysis for health policy. Methods: We firstly compute the weights of the SF12 physical and mental health measure for the Malawian population using principal component analysis on a sample of 2838 adults from wave four (2006) of Malawian Longitudinal Study of Aging (MLSFH). We secondly test the construct validity of our computed and the USpopulation weighted SF12 measures using regression analysis and Fixed Effect estimation on waves four, seven (2012) and eight (2013) of the MLSFH. Finally, we use a Malawian cash transfer programme to exemplify the implications of using US-and Malawi-weighted SF12 mental health measures in policy evaluation. Results: We find that the Malawian SF12 health measure weighted by our computed Malawian population weights is strongly associated with other mental health measures (Depression:-0.501, p = < 0.001; Anxiety:-1.755; p = < 0.001) and shows better construct validity in comparison to the US-weighted SF12 mental health component (rs = 0.675 versus rs = 0.495). None of the SF12 measures shows strong associations with other measures of physical health. The estimated average effect of the cash transfer is significant when using the Malawi-weighted SF12 mental health measure (treatment effect: 1.124; p = < 0.1), but not when using the US-weighted counterpart (treatment effect: 1.129; p > 0.1). The weightings affect the size of the impacts across mental health quantiles suggesting that the weighting scheme matters for empirical health policy analysis. Conclusion: Mental health shows more pronounced associations with the physical health dimension in a Low-Income Country like Malawi compared to the US. This is important for the construct validity of the SF12 health measures and has strong implications in health policy analysis. Further analysis is required for the physical health dimension of the SF12.

ObjectivesTo study the characteristics of UK individuals identified with non-diabetic hyperglycaemia (NDH) and their conversion rates to type 2 diabetes mellitus (T2DM) from 2000 to 2015, using the Clinical Practice Research Datalink.DesignCohort study.SettingsUK primary Care Practices.ParticipantsElectronic health records identified 14 272 participants with NDH, from 2000 to 2015.Primary and secondary outcome measuresBaseline characteristics and conversion trends from NDH to T2DM were explored. Cox proportional hazards models evaluated predictors of conversion.ResultsCrude conversion was 4% within 6 months of NDH diagnosis, 7% annually, 13% within 2 years, 17% within 3 years and 23% within 5 years. However, 1-year conversion fell from 8% in 2000 to 4% in 2014. Individuals aged 45–54 were at the highest risk of developing T2DM (HR 1.20, 95% CI 1.15 to 1.25— compared with those aged 18–44), and the risk reduced with older age. A body mass index (BMI) above 30 kg/m2 was strongly associated with conversion (HR 2.02, 95% CI 1.92 to 2.13—compared with those with a normal BMI). Depression (HR 1.10, 95% CI 1.07 to 1.13), smoking (HR 1.07, 95% CI 1.03 to 1.11—compared with non-smokers) or residing in the most deprived areas (HR 1.17, 95% CI 1.11 to 1.24—compared with residents of the most affluent areas) was modestly associated with conversion.ConclusionAlthough the rate of conversion from NDH to T2DM fell between 2010 and 2015, this is likely due to changes over time in the cut-off points for defining NDH, and more people of lower diabetes risk being diagnosed with NDH over time. People aged 45–54, smokers, depressed, with high BMI and more deprived are at increased risk of conversion to T2DM.

Background: Mental health and poverty are strongly interlinked. There is a gap in the literature on the effects of poverty alleviation programmes on mental health. We aim to fill this gap by studying the effect of an exogenous income shock generated by the Child Support Grant, South Africa's largest Unconditional Cash Transfer (UCT) programme, on mental health. Methods: We use biennial data on 10,925 individuals from the National Income Dynamics Study between 2008 and 2014. We exploit the programme's eligibility criteria to estimate instrumental variable Fixed Effects models. Results: We find that receiving the Child Support Grant improves adult mental health by 0.822 points (on a 0-30 scale), 4.1% of the sample mean. Conclusion: Our findings show that UCT programmes have strong mental health benefits for the poor adult population.