Cohort profile: the Healthy Life in an Urban Setting (HELIUS) study in Amsterdam, The Netherlands

Purpose

Ethnic minority groups usually have a more unfavourable disease risk profile than the host population. In Europe, ethnic inequalities in health have been observed in relatively small studies, with limited possibilities to explore underlying causes. The aim of the Healthy Life in an Urban Setting (HELIUS) study is to investigate the causes of (the unequal burden of) diseases across ethnic groups, focusing on three disease categories: cardiovascular diseases, mental health and infectious diseases.

Participants

The HELIUS study is a prospective cohort study among six large ethnic groups living in Amsterdam, the Netherlands. Between 2011 and 2015, a total 24 789 participants (aged 18–70 years) were included at baseline. Similar-sized samples of individuals of Dutch, African Surinamese, South-Asian Surinamese, Ghanaian, Turkish and Moroccan origin were included. Participants filled in an extensive questionnaire and underwent a physical examination that included the collection of biological samples (biobank).

Findings to date

Data on physical, behavioural, psychosocial and biological risk factors, and also ethnicity-specific characteristics (eg, culture, migration history, ethnic identity, socioeconomic factors and discrimination) were collected, as were measures of health outcomes (cardiovascular, mental health and infections). The first results have confirmed large inequalities in health between ethnic groups, such as diabetes and depressive symptoms, and also early markers of disease such as arterial wave reflection and chronic kidney disease, which can only just partially be explained by inequalities in traditional risk factors, such as obesity and socioeconomic status. In addition, the first results provided important clues for targeting prevention and healthcare.

Future plans

HELIUS will be used for further research on the underlying causes of ethnic differences in health. Follow-up data will be obtained by repeated measurements and by linkages with existing registries (eg, hospital data, pharmacy data and insurance data).

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