Social inequality and diabetes mellitus - developments over time among the adult population in Germany

Intersectional analysis of social disparities in type 2 diabetes risk among adults in Germany: results from a nationwide population-based survey

BACKGROUND

Differences in type 2 diabetes risk have been reported for several sociodemographic determinants including sex/gender or socioeconomic status. From an intersectional perspective, it is important to not only consider the role of social dimensions individually, but also their intersections. This allows for a deeper understanding of diabetes risk and preventive needs among diverse population groups.

METHODS

As an intersectionality-informed approach, multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was used in a population-based sample of adults without known diabetes in Germany from the cross-sectional survey "Disease knowledge and information needs- Diabetes mellitus (2017)". Diabetes risk was assessed by the German Diabetes Risk Score (GDRS, range 0-122 points), estimating the individual risk of developing type 2 diabetes within the next 5 years based on established self-reported risk factors. Nesting individuals in 12 intersectional strata defined by combining sex/gender, educational level, and history of migration, we calculated measures to quantify the extent to which individual differences in diabetes risk were explained at strata level, and how much this was due to additive or multiplicative intersectional effects of social determinants.

RESULTS

Drawing on data of 2,253 participants, we found good discriminatory accuracy of intersectional strata (variance partition coefficient = 14.00% in the simple intersectional model). Model-predicted GDRS means varied between 29.97 (corresponding to a "low risk" of < 2%) in women with high educational level and a history of migration, and 52.73 ("still low risk" of 2-5%) in men with low educational level without a history of migration. Variance in GDRS between strata was mainly explained by additive effects of social determinants (proportional change in variance to intersectional interaction model = 77.95%) with being male and having low educational level being associated with higher GDRS. There was no evidence of multiplicative effects in individual strata.

CONCLUSIONS

Type 2 diabetes risk differed between intersectional strata and can to some extent be explained at strata level. The role of intersectional effects was minor and needs to be further investigated. Findings suggest a need for specific preventive measures targeted at large groups with increased diabetes risk, such as men and persons with low educational level.

Population with an increased risk of severe COVID-19 in Germany. Analyses from GEDA 2019/2020-EHIS

Only a minority of people who test positive for COVID-19 develop a severe or critical form of the disease. Many of these have risk factors such as old age or pre-existing conditions and, therefore, are at the focus of protective measures. This article determines the number of people at risk in Germany and differentiates them according to age, sex, education, household type and federal state. The analyses presented here are based on data from the German Health Update (GEDA) 2019/2020-EHIS, which was carried out as a nationwide cross-sectional telephone-based survey between April 2019 and October 2020. The definition of being at increased risk of severe COVID-19 is primarily based on a respondent’s age and the presence of pre-existing conditions. Around 36.5 million people in Germany are at an increased risk of developing severe COVID-19. Of these, 21.6 million belong to the high-risk group. An above-average number of people at risk live alone. The prevalence of an increased risk is higher among middle-aged men than among women of the same age, and significantly higher among people with a low level of education than among people with a high level of education. The highest proportion of people with an increased risk live in Saarland and in the eastern German federal states. When fighting the pandemic, it is important to account for the fact that more than half of the population aged 15 or over is at increased risk of severe illness. Moreover, the regional differences in risk burden should be taken into account when planning interventions.