[Regional Deprivation in Germany: Nation-wide Analysis of its Association with Mortality Using the German Index of Multiple Deprivation (GIMD)]

The impact of regional deprivation on stroke incidence, treatment, and mortality in Germany

BACKGROUND

Regional deprivation has been shown to be an influential factor in stroke incidence risk. However, there is a paucity of knowledge on regional differences in stroke incidence and mortality in Germany.

METHODS

We assessed data from the Diagnosis Related Groups statistics (2016-2019) and the German Federal Registry of Physicians (2019). Negative binomial regression analysis was used to examine the association between the German Index of Multiple Deprivation 2015 covering 401 districts and district-free cities in Germany and stroke incidence, treatment, and mortality.

RESULTS

The adjusted rate ratios of stroke incidence and mortality with the highest deprivation level compared with the least deprived area were 1.161 (95% CI [1.143, 1.179]) and 1.193 (95% CI [1.148, 1.239]), respectively. Moreover, this study revealed that physician density was higher in district-free cities compared to districts.

CONCLUSIONS

Our results indicate that regional deprivation is associated with incident and mortality cases of stroke, necessitating a more targeted approach to stroke prevention in deprived regions.

Availability of open data for spatial public health research

Background: Preventive and health-promoting policies can guide (place- and space-specific) factors influencing human health, such as the physical and social environment. Required is data that can lead to a more nuanced decision-making process and identify both existing and future challenges. Along with the rise of new technologies, and thus the multiple opportunities to use and process data, new options have emerged to measure and monitor factors that affect health. Thus, in recent years, several gateways for open data (including governmental and geospatial data) have become available. At present, an increasing number of research institutions as well as (state and private) companies and citizens' initiatives are providing data. However, there is a lack of overviews covering the range of such offerings regarding health. In particular, for geographically differentiated analyses, there are challenges related to data availability at different spatial levels and the growing number of data providers. Objectives: This paper aims to provide an overview of open data resources available in the context of space and health to date. It also describes the technical and legal conditions for using open data. Results: An up-to-date summary of results including information on relevant data access and terms of use is provided along with a web visualization. All data is available for further use under an open license.

Social Determinants of Remaining Life Expectancy at Age 60: A District-Level Analysis in Germany

Remaining life expectancy at age 60 (in short: RLE) is an important indicator of the health status of a population's elders. Until now, RLE has not been thoroughly investigated at the district level in Germany. In this study we analyzed, based on recent publicly available data (2015-2017), and for men and women separately, how large the RLE differences were in Germany across the 401 districts. Furthermore, we examined a wide range of potential social determinants in terms of their bivariate and multivariate (i.e., partial) impact on men's and women's RLE. Men's district-level RLE ranged between 19.89 and 24.32 years, women's district-level RLE between 23.67 and 27.16 years. The best single predictor both for men's and women's RLE at district level was 'proportion of employees with academic degree' with standardized partial regression coefficients of 0.42 (men) and 0.51 (women). Second and third in rank were classic economic predictors, such as 'household income' (men), 'proportion of elder with financial elder support' (women), and 'unemployment' (men and women). Indicators expressing the availability of medical services and staffing levels of nursing homes and services had at best a marginal partial impact. This study contributes to the growing body of evidence that a population's educational level is a decisive determinant of population health resp. life expectancy in contemporary industrialized societies.

Regional Deprivation, Stroke Incidence, and Stroke Care

BACKGROUND

Regional deprivation can increase the risk of illness and adversely affect care outcomes. In this study, we investigated for the German state of Rhineland-Palatinate whether spatial-structural disadvantages are associated with an increased frequency of ischemic stroke and with less favorable care outcomes.

METHODS

We compared billing data from DRG statistics (2008-2017) and quality assurance data (2017) for acute ischemic stroke with the German Index of Multiple Deprivation 2010 (GIMD 2010) for the 36 districts (Landkreise) and independent cities (i.e., cities not belonging to a district) in Rhineland-Palatinate using correlation analyses, a Poisson regression analysis, and logistic regression analyses.

RESULTS

The age-standardized stroke rates (ASR) ranged from 122 to 209 per 100 000 inhabitants, while the GIMD 2010 ranged from 4.6 to 47.5; the two values were positively correlated (Spearman's ρ = 0.47; 95% confidence interval [0.16; 0.85]). In 2017, mechanical thrombectomies were performed more commonly (5.7%) in the first GIMD 2010 quartile of the regional areas (i.e., in the least deprived areas) than in the remaining quartiles (4.2-4.6%). The intravenous thrombolysis rates showed no differences from one GIMD 2010 quartile to another. Severe neurological deficits (National Institutes of Health Stroke Scale ≥ 5) on admission to the hospital were slightly more common in the fourth quartile (i.e., in the most deprived areas), while antiplatelet drugs and statins were somewhat less commonly ordered on discharge in those areas than in the first quartile.

CONCLUSION

These findings document a relationship between regional deprivation and the occurrence of acute ischemic stroke. Poorer GIMD 2010 scores were associated with worse care outcomes in a number of variables, but the absolute differences were small.

A greedy stacking algorithm for model ensembling and domain weighting

OBJECTIVE

Because it is impossible to know which statistical learning algorithm performs best on a prediction task, it is common to use stacking methods to ensemble individual learners into a more powerful single learner. Stacking algorithms are usually based on linear models, which may run into problems, especially when predictions are highly correlated. In this study, we develop a greedy algorithm for model stacking that overcomes this issue while still being very fast and easy to interpret. We evaluate our greedy algorithm on 7 different data sets from various biomedical disciplines and compare it to linear stacking, genetic algorithm stacking and a brute force approach in different prediction settings. We further apply this algorithm on a task to optimize the weighting of the single domains (e.g., income, education) that build the German Index of Multiple Deprivation (GIMD) to be highly correlated with mortality.

RESULTS

The greedy stacking algorithm provides good ensemble weights and outperforms the linear stacker in many tasks. Still, the brute force approach is slightly superior, but is computationally expensive. The greedy weighting algorithm has a variety of possible applications and is fast and efficient. A python implementation is provided.

[Socioeconomic status and health insurance expenditures for children and adolescents with conduct disorder : An analysis of statutory health insurance data]

BACKGROUND

For various psychiatric and somatic disorders, there is evidence of an association between patients' socioeconomic status (SES), healthcare utilisation, and the resulting costs. In the field of child and adolescent psychiatric disorders, studies on this topic are lacking.

OBJECTIVES

To exploratively analyse the association of healthcare expenditures for children and adolescents with conduct disorder (including oppositional-defiant disorder) - one of the most prevalent child and adolescent psychiatric disorders - and SES.

MATERIALS AND METHODS

The analysis is based on routine data from the German statutory health insurance company AOK Nordost for the calendar year 2011, covering 6461 children and adolescents (age 5-18 years) with an ICD-10 diagnosis of conduct disorder. The insureds' SES was estimated indirectly, based on the social structure of the postcode area, using the German Index of Multiple Deprivation (Mecklenburg-Vorpommern, Brandenburg), and the Berliner Sozialindex I (Berlin), respectively. From the two indices, quintiles were derived. Based on these quintiles, average costs per case for the following cost types were analysed: inpatient healthcare, outpatient healthcare (general practitioners, paediatricians, child and adolescent psychiatrists, child and adolescent psychotherapists), and prescribed medication.

RESULTS

There was no significant functional association between SES and healthcare costs for any of the analysed cost types.

CONCLUSIONS

In contrast to findings in adults, this study on children and adolescents with conduct disorders did not reveal an association between SES and healthcare costs. Within this group of patients, social inequality does not seem to have a significant influence on healthcare utilisation in Germany.

Is there an association between spatial accessibility of outpatient care and utilization? Analysis of gynecological and general care

Background

In rural regions with a low population density, distances to health care providers as well as insufficient public transport may be barriers for the accessibility of health care. In this analysis it was examined whether the accessibility of gynecologists and GPs, measured as travel time both by car and public transport has an influence on the utilization of health care in the rural region of Western Pomerania in Northern Germany.

Methods

Utilization data was obtained from the population based Study of Health in Pomerania (SHIP). Utilization was operationalized by the parameter “at least one physician visit during the last 12 months”. To determine travel times by car and by public transport, network analyses were conducted in a Geographic Information System (GIS). Multivariate logistic regression models were calculated to identify determinants for the utilization of gynecologists and GPs.

Results

There is no significant association between the accessibility by car or public transport and the utilization of gynecologists and GPs. Significant predictors for the utilization of gynecologists in the regression model including public transport are age (OR 0.960, 95% CI 0.950–0.971, p < 0.0001), social class (OR 1.137, 95% CI 1.084–1.193, p < 0.0001) and having persons ≥18 years in the household (OR 2.315, 95% CI 1.116–4.800, p = 0.0241).

Conclusions

In the examined region less utilization of gynecologists is not explainable with long travel times by car or public transport.

Who is where at risk for Chronic Obstructive Pulmonary Disease? A spatial epidemiological analysis of health insurance claims for COPD in Northeastern Germany

Background

Chronic obstructive pulmonary disease (COPD) has a high prevalence rate in Germany and a further increase is expected within the next years. Although risk factors on an individual level are widely understood, only little is known about the spatial heterogeneity and population-based risk factors of COPD. Background knowledge about broader, population-based processes could help to plan the future provision of healthcare and prevention strategies more aligned to the expected demand. The aim of this study is to analyze how the prevalence of COPD varies across northeastern Germany on the smallest spatial-scale possible and to identify the location-specific population-based risk factors using health insurance claims of the AOK Nordost.

Methods

To visualize the spatial distribution of COPD prevalence at the level of municipalities and urban districts, we used the conditional autoregressive Besag–York–Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific ecological risk factors for COPD.

Results

The sex- and age-adjusted prevalence of COPD was 6.5% in 2012 and varied widely across northeastern Germany. Population-based risk factors consist of the proportions of insurants aged 65 and older, insurants with migration background, household size and area deprivation. The results of the GWR model revealed that the population at risk for COPD varies considerably across northeastern Germany.

Conclusion

Area deprivation has a direct and an indirect influence on the prevalence of COPD. Persons ageing in socially disadvantaged areas have a higher chance of developing COPD, even when they are not necessarily directly affected by deprivation on an individual level. This underlines the importance of considering the impact of area deprivation on health for planning of healthcare. Additionally, our results reveal that in some parts of the study area, insurants with migration background and persons living in multi-persons households are at elevated risk of COPD.

Exploring the small-scale spatial distribution of hypertension and its association to area deprivation based on health insurance claims in Northeastern Germany

BACKGROUND

Hypertension is one of the most frequently diagnosed chronic conditions in Germany. Targeted prevention strategies and allocation of general practitioners where they are needed most are necessary to prevent severe complications arising from high blood pressure. However, data on chronic diseases in Germany are mostly available through survey data, which do not only underestimate the actual prevalence but are also only available on coarse spatial scales. The discussion of including area deprivation for planning of healthcare is still relatively young in Germany, although previous studies have shown that area deprivation is associated with adverse health outcomes, irrespective of individual characteristics. The aim of this study is therefore to analyze the spatial distribution of hypertension at very fine geographic scales and to assess location-specific associations between hypertension, socio-demographic population characteristics and area deprivation based on health insurance claims of the AOK Nordost.

METHODS

To visualize the spatial distribution of hypertension prevalence at very fine geographic scales, we used the conditional autoregressive Besag-York-Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific association of hypertension to area deprivation and further socio-demographic population characteristics.

RESULTS

The sex- and age-adjusted prevalence of hypertension was 33.1% in 2012 and varied widely across northeastern Germany. The main risk factors for hypertension were proportions of insurants aged 45-64, 65 and older, area deprivation and proportion of persons commuting to work outside their residential municipality. The GWR model revealed important regional variations in the strength of the examined associations.

CONCLUSION

Area deprivation has only a significant and therefore direct influence in large parts of Mecklenburg-West Pomerania. However, the spatially varying strength of the association between demographic variables and hypertension indicates that there also exists an indirect effect of area deprivation on the prevalence of hypertension. It can therefore be expected that persons ageing in deprived areas will be at greater risk of hypertension, irrespective of their individual characteristics. The future planning and allocation of primary healthcare in northeastern Germany would therefore greatly benefit from considering the effect of area deprivation.

The Non-Linear Relationship between BMI and Health Care Costs and the Resulting Cost Fraction Attributable to Obesity

This study aims to analyse the non-linear relationship between Body Mass Index (BMI) and direct health care costs, and to quantify the resulting cost fraction attributable to obesity in Germany. Five cross-sectional surveys of cohort studies in southern Germany were pooled, resulting in data of 6757 individuals (31–96 years old). Self-reported information on health care utilisation was used to estimate direct health care costs for the year 2011. The relationship between measured BMI and annual costs was analysed using generalised additive models, and the cost fraction attributable to obesity was calculated. We found a non-linear association of BMI and health care costs with a continuously increasing slope for increasing BMI without any clear threshold. Under the consideration of the non-linear BMI-cost relationship, a shift in the BMI distribution so that the BMI of each individual is lowered by one point is associated with a 2.1% reduction of mean direct costs in the population. If obesity was eliminated, and the BMI of all obese individuals were lowered to 29.9 kg/m², this would reduce the mean direct costs by 4.0% in the population. Results show a non-linear relationship between BMI and health care costs, with very high costs for a few individuals with high BMI. This indicates that population-based interventions in combination with selective measures for very obese individuals might be the preferred strategy.

[Social disparities in outpatient and inpatient care: An overview of current findings in Germany]

There is controversy about social disparities in healthcare services in Germany, but a differentiated analysis regarding various dimensions of healthcare is lacking. This narrative review intends to summarize conceptually the current state of research and draw subsequent conclusions. Separated into access, utilization and quality, the findings of social inequality in outpatient and inpatient care in Germany are summarized. Besides the common individual indicators of socioeconomic status (SES), regional deprivation and health insurance status are also included. Despite methodical diversity, the results show that healthcare inequalities due to SES exist, but not universally. Furthermore, there is a differentiated pattern respecting separate dimensions of healthcare. Concerning access (e.g. waiting times, co-payments) lower status groups and patients covered by statutory health insurance are deprived. Higher utilization becomes apparent among higher status groups and privately insured patients in terms of specialist consultations and prevention services. The findings regarding quality of process and outcome differ depending on quality indicator and disease. In different dimensions of medical healthcare, social disparities still exist, though the impact on health remains unclear for some types of healthcare inequalities. Moreover, it is often difficult to conclude from unequal outcome quality the inequalities of healthcare. Depending on access, utilization and quality, separate interventions for reducing these disparities are to be introduced.