Background: Regional and country-specific cardiovascular risk algorithms have been developed to improve CVD risk prediction. But it is unclear whether migrants’ country-of-residence or country-of-birth algorithms agree in stratifying the CVD risk of these populations. We evaluated the risk stratification by the different algorithms, by comparing migrant country-of-residence-specific scores to migrant country-of-birth-specific scores for ethnic minority populations in the Netherlands. Method: data from the HELIUS study was used in estimating the CVD risk scores for participants using five laboratory-based (Framingham, Globorisk, Pool Cohort Equation II, SCORE II, and WHO II) and three nonlaboratory-based (Framingham, Globorisk, and WHO II) risk scores with the risk chart for the Netherlands. For the Globorisk, WHO II, and SCORE II risk scores, we also computed the risk scores using risk charts specified for the migrant home country. Risk categorization was first done according to the specification of the risk algorithm and then simplified to low (green), moderate (yellow and orange), and high risk (red). Results: we observed differences in risk categorization for different risk algorithms ranging from 0% (Globorisk) to 13% (Framingham) for the high-risk category, as well as differences in the country-of-residence- and country-of-birth-specific scores. Agreement between different scores ranged from none to moderate. We observed a moderate agreement between the Netherlands-specific SCORE II and the country-of-birth SCORE II for the Turkish and a nonagreement for the Dutch Moroccan population. Conclusion: disparities exist in the use of the country-of-residence-specific, as compared to the country-of-birth, risk algorithms among ethnic minorities living in the Netherlands. Hence, there is a need for further validation of country-of-residence- and country-of-birth-adjusted scores to ascertain appropriateness and reliability.

Problematic alcohol use is argued to develop according to complex system principles, where clinical phenomena emerge through a bidirectional, (non-)linear interplay between psychological symptoms, (neuro-)biological factors, and environmental components including sociodemographic determinants, for example, ethnic, religious, and socioeconomic variables. These principles can be modelled through the network perspective. Research remains uncertain how ethnic, religious, and socioeconomic variables influence and are influenced by symptoms of alcohol use disorder, and how these interactions vary between ethnic groups. To investigate these open-standing questions, we conduct an exploratory network analysis in a Bayesian framework in a large, multi-ethnic, urban sample in the Netherlands, the HELIUS study (N = 22,164). Our analyses revealed that sociodemographic factors were differentially related to alcohol use symptoms, with religion being negatively associated to binge drinking and adverse events due to drinking (e.g., feelings of guilt). Sex differences were revealed: higher education buffered against more adverse AUD symptoms for females and being employed for males. Stratifying our analyses by ethnicity, results suggested a different importance of sociodemographic determinants for alcohol use symptoms across ethnic groups; whereas for some subgroups all factors were important others showed hardly any interactions. Considering the trend of urban areas becoming increasingly diverse, our results point to the finding that sociodemographic factors are important to acknowledge for particular alcohol use symptoms. Tailored sex-specific prevention and intervention strategies should be considered and evaluated for urban ethnic minority communities.

Background Although risk factors for differences in SARS-CoV-2 infections between migrant and non-migrant populations in high income countries have been identified, their relative contributions to these SARS-CoV-2 infections, which could aid in the preparation for future viral pandemics, remain unknown. We investigated the relative contributions of pre-pandemic factors and intra-pandemic activities to differential SARS-CoV-2 infections in the Netherlands by migration background (Dutch, African Surinamese, South-Asian Surinamese, Ghanaians, Turkish, and Moroccan origin). Methods We utilized pre-pandemic (2011–2015) and intra-pandemic (2020–2021) data from the HELIUS cohort, linked to SARS-CoV-2 PCR test results from Public Health Service of Amsterdam (GGD Amsterdam). Pre-pandemic factors included socio-demographic, medical, and lifestyle factors. Intra-pandemic activities included COVID-19 risk aggravating and mitigating activities such as physical distancing, use of face masks, and other similar activities. We calculated prevalence ratios (PRs) in the HELIUS population that was merged with GGD Amsterdam PCR test data using robust Poisson regression (SARS-CoV-2 PCR test result as outcome, migration background as predictor). We then obtained the distribution of migrant and non-migrant populations in Amsterdam as of January 2021 from Statistics Netherlands. The migrant populations included people who have migrated themselves as well as their offspring. We used PRs and the population distributions to calculate population attributable fractions (PAFs) using the standard formula. We used age and sex adjusted models to introduce pre-pandemic factors and intra-pandemic activities, noting the relative changes in PAFs. Results From 20,359 eligible HELIUS participants, 8,595 were linked to GGD Amsterdam PCR test data and included in the study. Pre-pandemic socio-demographic factors (especially education, occupation, and household size) resulted in the largest changes in PAFs when introduced in age and sex adjusted models (up to 45%), followed by pre-pandemic lifestyle factors (up to 23%, especially alcohol consumption). Intra-pandemic activities resulted in the least changes in PAFs when introduced in age and sex adjusted models (up to 16%). Conclusion Interventions that target pre-pandemic socio-economic status and other drivers of health inequalities between migrant and non-migrant populations are urgently needed at present to better prevent infection disparities in future viral pandemics.