Separate and combined effects of individual and neighbourhood socio-economic disadvantage on health-related lifestyle risk factors:a multilevel analysis

BACKGROUND: Socio-economic disadvantage at both individual and neighbourhood levels has been found to be associated with single lifestyle risk factors. However, it is unknown to what extent their combined effects contribute to a broad lifestyle profile. We aimed to (i) investigate the associations of individual socio-economic disadvantage (ISED) and neighbourhood socio-economic disadvantage (NSED) in relation to an extended score of health-related lifestyle risk factors (lifestyle risk index); and to (ii) investigate whether NSED modified the association between ISED and the lifestyle risk index. METHODS: Of 77 244 participants [median age (IQR): 46 (40-53) years] from the Lifelines cohort study in the northern Netherlands, we calculated a lifestyle risk index by scoring the lifestyle risk factors including smoking status, alcohol consumption, diet quality, physical activity, TV-watching time and sleep time. A higher lifestyle risk index was indicative of an unhealthier lifestyle. Composite scores of ISED and NSED based on a variety of socio-economic indicators were calculated separately. Linear mixed-effect models were used to examine the association of ISED and NSED with the lifestyle risk index and to investigate whether NSED modified the association between ISED and the lifestyle risk index by including an interaction term between ISED and NSED. RESULTS: Both ISED and NSED were associated with an unhealthier lifestyle, because ISED and NSED were both positively associated with the lifestyle risk index {highest quartile [Q4] ISED beta-coefficient [95% confidence interval (CI)]: 0.64 [0.62-0.66], P < 0.001; highest quintile [Q5] NSED beta-coefficient [95% CI]: 0.17 [0.14-0.21], P < 0.001} after adjustment for age, sex and body mass index. In addition, a positive interaction was found between NSED and ISED on the lifestyle risk index (beta-coefficient 0.016, 95% CI: 0.011-0.021, Pinteraction < 0.001), which indicated that NSED modified the association between ISED and the lifestyle risk index; i.e. the gradient of the associations across all ISED quartiles (Q4 vs Q1) was steeper among participants residing in the most disadvantaged neighbourhoods compared with those who resided in the less disadvantaged neighbourhoods. CONCLUSIONS: Our findings suggest that public health initiatives addressing lifestyle-related socio-economic health differences should not only target individuals, but also consider neighbourhood factors

Benčmarkovanje ekonomija zapadnog Balkana

Abstract: The aim of this paper is to analyse the relative positions of Western Balkan countries and to determine the differences or similarities in the results based on survey data (of international institutions: EBRD, Worl

Cost utility analysis of everolimus in the treatment of metastatic renal cell cancer in the Netherlands

Objectives: Metastatic renal cell cancer (mRCC) is becoming an important part of Dutch health care expenditure due to expensive pharmaceutical options for disease control and lack of adequate prevention methods. New targeted therapeutics, such as sunitinib, sorafenib and everolimus, have recently emerged with relevant benefits on progression-free survival (PFS) for mRCC patients. This study aims to assess the cost-effectiveness of the most recent of these introductions, i.e. everolimus, in comparison to best supportive care in second line treatment of mRCC patients in The Netherlands. Methods: A Markov model was designed in line with Dutch treatment protocols. Transitions between health states were modeled by timedependent probabilities extracted from published Kaplan-Meier curves for PFS and overall survival (OS). The cohorts were followed over 18 cycles, each cycle lasting 8 weeks. Annual discount rates of 1.5% for health and 4% for costs were applied and a health-care perspective was taken. One-way and probabilistic sensitivity analyses (PSA) were performed to test the robustness and uncertainty around the base-case estimate. Results: The incremental cost-effectiveness ratio (ICER) for everolimus was esimated at € 92,258/QALY. Sensitivity analysis identified the hazard multiplier, an estimate of OS gain, as the main driver of everolimus' cost-effectiveness. Through PSA a wide 95% confidence interval around the base-case ICER estimate was revealed (€ 49,677 - € 453,941/QALY). Additionally, at the threshold of three times GDP per capita (€ 95,700 in The Netherlands) everolimus had a 54% probability of being cost-effective. Conclusions: The base-case ICER was just below the upper cost-effectiveness limit recommended by WHO, indicating that everolimus might be a cost-effective option in the Dutch setting. However, reasonable uncertainty of the main finding resulted from everolimus' unpredictable gain in OS. Efforts should be undertaken to perform an integral assessment of the economic attractiveness of all current and new therapeutics in mRCC