Socioeconomic IneQuality in Exposure to environmental Risk factors in Sweden (SIQER) - air pollution, traffic noise and access to green space in low- and high income areas

Research problems and specific questionsSocioeconomic and sociodemographic factors (education, income, occupation, age, gender, country of birth) are associated with lifestyle e.g. smoking, and health risks. Life style factors are related to cancer, metabolic and cardiovascular diseases.

Air pollution and traffic noise exposures are also risk factors here, but the association between exposure and socioeconomic status is complex: those with low income may live close to large roads with high exposures, or in low exposure suburbs close to green areas.

This, and to what extent health is affected by socioeconomic and environmental factors, have rarely been studied in Sweden.

We can, in 6 Swedish cities, investigate:-How are socioeconomic factors associated with exposure to air pollution, traffic noise and access to green areas?-Is the association with exposure strongest for individual or area-level socioeconomic factors?-Have the associations changed over time, and do they differ between cities and with degree of urbanization?-When moving to another area, does the change in exposure differ between socioeconomic groups?   -How does socioeconomic status modify the associations between environmental exposures and health/early indications of ill health (hypertension, diabetes, obesity)?Data and methodWe use the population-based SCAPIS cohort (30,000 persons, 6 cities), with socioeconomic, sociodemographic, health data and environmental exposure.

Address history (2000-2018) enables assessment of air pollution, traffic noise, greenness, and area-level socioeconomic markers.The health impact is evaluated through diagnoses and biomarkers (hypertension, diabetes, obesity, cholesterol).

Also, health effects are illustrated by combining our results (exposure-socioeconomic status) with risk functions for exposure and important health outcomes.Multilevel analysis is used, with individuals nested within areas.

The observations are weighted to adjust for differences in response rates related to age, sex and education.Plan for project realizationThe SCAPIS cohort contains data on individual socioeconomic status, life style, diseases and biomarkers. Environmental exposures are available from other projects.

Residential area socioeconomic status is defined using DeSO data (Statistics Sweden).RelevancePhysical environment inequality affects health.

The project investigates associations between environmental exposure and socioeconomy, and the relative impact on health, in Sweden.