Quality of care could be influenced by individual socio-economic status (SES) and by residential area deprivation. The objective is to synthesize the current evidence regarding inequalities in health care for patients with Type 2 diabetes mellitus (Type 2 DM). The systematic review focuses on inequalities concerning process (e.g. measurement of HbA1c, i.e. glycolised haemoglobin) and intermediate outcome indicators (e.g. HbA1c level) of Type 2 diabetes care. In total, of n = 886 publications screened, n = 21 met the inclusion criteria. A wide variety of definitions for ‘good quality diabetes care’, regional deprivation and individual SES was observed. Despite differences in research approaches, there is a trend towards worse health care for patients with low SES, concerning both process of care and intermediate outcome indicators. Patients living in deprived areas less often achieve glycaemic control targets, tend to have higher blood pressure (BP) and worse lipid profile control. The available evidence clearly points to the fact that socio-economic inequalities in diabetes care do exist. Low individual SES and residential area deprivation are often associated with worse process indicators and worse intermediate outcomes, resulting in higher risks of microvascular and macrovascular complications. These inequalities exist across different health care systems. Recommendations for further research are provided.

Although socioeconomic inequalities in cancer survival have been demonstrated both within and between countries, evidence on the variation of the inequalities over time past diagnosis is sparse. Furthermore, no comprehensive analysis of socioeconomic differences in cancer survival in Germany has been conducted. Therefore, we analyzed variations in cancer survival for patients diagnosed with one of the 25 most common cancer sites in 1997–2006 in ten population‐based cancer registries in Germany (covering 32 million inhabitants). Patients were assigned a socioeconomic status according to the district of residence at diagnosis. Period analysis was used to derive 3‐month, 5‐year and conditional 1‐year and 5‐year age‐standardized relative survival for 2002–2006 for each deprivation quintile in Germany. Relative survival of patients living in the most deprived district was compared to survival of patients living in all other districts by model‐based period analysis. For 21 of 25 cancer sites, 5‐year relative survival was lower in the most deprived districts than in all other districts combined. The median relative excess risk of death over the 25 cancer sites decreased from 1.24 in the first 3 months to 1.16 in the following 9 months to 1.08 in the following 4 years. Inequalities persisted after adjustment for stage. These major regional socioeconomic inequalities indicate a potential for improving cancer care and survival in Germany. Studies on individual‐level patient data with access to treatment information should be conducted to examine the reasons for these socioeconomic inequalities in cancer survival in more detail.

Deprivationsindizes stellen wertvolle Instrumente zur Analyse regionaler Effekte auf die Gesundheit der Bevölkerung dar. Bei fehlenden sozioökonomischen Individualdaten können diese Indizes auch als Surrogat verwendet werden. Im Vereinigten Königreich sind derartige regionale Deprivationsindizes fester Bestandteil der Public Health – Diskussion, in Deutschland dagegen steht diese Entwicklung erst am Anfang. Unser Ziel war es, auf Grundlage einer etablierten britischen Methode einen kleinräumigen und mehrdimensionalen Index Multipler Deprivation (IMD) für Deutschland zu entwickeln. Als Modellregion wählten wir das Bundesland Bayern mit seinen n=2 056 Gemeinden. Unter Verwendung soziodemografischer, sozioökonomischer und umweltrelevanter Daten der amtlichen Statistik entwickelten wir hierfür einen Bayerischen Index Multipler Deprivation (BIMD). Um die Eignung dieses Index für epidemiologische Analysen zu prüfen, führten wir anschließend sowohl eine Korrelationsanalyse (Korrelationskoeffizient nach Spearman) als auch eine Poisson-Regression unter Verwendung von Daten zur vorzeitigen Mortalität (Altersgruppe < 65 Jahre) sowie zur Gesamtmortalität (alle Altersgruppen) durch. Die Korrelationsanalyse zeigte einen positiven signifikanten Zusammenhang zwischen regionaler Deprivation und Mortalität. Die Poisson-Regression ergab einen klaren Gradienten, d. h. das Mortalitätsrisiko stieg mit zunehmender regionaler Deprivation stufenweise an. Verglichen mit den Gemeinden im Quintil mit der niedrigsten Deprivation war das relative Risiko bei den Gemeinden mit der höchsten Deprivation deutlich größer, sowohl bei der vorzeitigen Mortalität [RR 1,49 (95% KI: 1,42 − 1,57)] als auch der Gesamtmortalität [RR 1,21 (95% KI: 1,18 − 1,25)]. Unter Verwendung des neu gebildeten Index konnte am Beispiel Bayerns gezeigt werden, dass höhere regionale Deprivation mit höherer Mortalität assoziiert ist. Dieser Index stellt somit ein neues und potentiell sehr nützliches Werkzeug für gesundheitswissenschaftliche Studien in Deutschland dar. Deprivation indices are valuable instruments for the analysis of regional effects on health. They may also be used as a surrogate when individual socioeconomic data are not available. These regional deprivation indices are integral parts of the public health discussion in the United Kingdom. In Germany, however, the discussion on this topic has just begun. Our aim was to develop a small-area based, multidimensional Index of Multiple Deprivation (IMD) for Germany, based on an established British method. We chose the German state of Bavaria with its n=2 056 communities as a model region. We used official sociodemographic, socioeconomic and environmental data and created a Bavarian Index of Multiple Deprivation (BIMD). In order to test the applicability of the BIMD in epidemiological analyses we then performed a correlation analysis (Spearman’s correlation coefficient) as well as a Poisson regression using data on premature mortality (< 65 years) and on total mortality (all age groups). The correlation analysis showed a positive and significant association between regional deprivation and mortality. The Poisson regression showed a clear gradient, i. e., we found a stepwise increase of mortality risk with increasing regional deprivation. Compared with communities in the lowest deprivation quintile, communities in the highest deprivation quintile showed a clearly higher mortality risk, both for premature mortality [RR 1.49 (95% CI: 1.42 − 1.57)] and for total mortality [RR 1.21 (95% CI: 1.18 − 1.25)]. Using this new index, we could demonstrate for communities in Bavaria that higher regional deprivation is associated with higher mortality. This Index of Multiple Deprivation is a new and potentially useful tool for epidemiological and public health related studies in Germany.

There is increasing evidence that prevention programmes for type 2 diabetes mellitus (T2DM) and obesity need to consider individual and regional risk factors. Our objective is to assess the independent association of area level deprivation with T2DM and obesity controlling for individual risk factors in a large study covering the whole of Germany. We combined data from two consecutive waves of the national health interview survey ‘GEDA’ conducted by the Robert Koch Institute in 2009 and 2010. Data collection was based on computer-assisted telephone interviews. After exclusion of participants <30 years of age and those with missing responses, we included n = 33,690 participants in our analyses. The outcome variables were the 12-month prevalence of known T2DM and the prevalence of obesity (BMI ≥30 kg/m²). We also controlled for age, sex, BMI, smoking, sport, living with a partner and education. Area level deprivation of the districts was defined by the German Index of Multiple Deprivation. Logistic multilevel regression models were performed using the software SAS 9.2. Of all men and women living in the most deprived areas, 8.6% had T2DM and 16.9% were obese (least deprived areas: 5.8% for T2DM and 13.7% for obesity). For women, higher area level deprivation and lower educational level were both independently associated with higher T2DM and obesity prevalence [highest area level deprivation: OR 1.28 (95% CI: 1.05–1.55) for T2DM and OR 1.28 (95% CI: 1.10–1.49) for obesity]. For men, a similar association was only found for obesity [OR 1.20 (95% CI: 1.02–1.41)], but not for T2DM. Area level deprivation is an independent, important determinant of T2DM and obesity prevalence in Germany. Identifying and targeting specific area-based risk factors should be considered an essential public health issue relevant to increasing the effectiveness of diabetes and obesity prevention.