Issue: Most studies related to neighbourhoods and health consider a limited number of factors, which may not convey the complexity of neighbourhoods on one side of the equation, and health on the other.
On the neighbourhood side of the equation, studies generally focus on the levels of income and/or education of people who live in a given area, along with measures like unemployment rates and number of single-parent households. Taken together, some or all of these measures are often termed ‘socio-economic status.’ In reality, however, health outcomes will be impacted by a broader range of factors. We wouldn’t describe a person using only one characteristic – we also need to look at the different layers and nuances that make up a given neighbourhood
On the health side of the equation, studies often look at the relationship between a neighbourhood and one particular health outcome (eg. diabetes). Since few, if any, environmental impacts on health are disease specific – for example, housing instability has been correlated to a range of physical and mental health impacts – this approach can serve to underplay the effects of negative conditions on health.
In addition, most studies start with a random sample of individuals, and then go back to find out where these individuals live. This design can result in too few participants in any single neighbourhood, making it difficult to tease out the relationship between neighbourhood factors and health and wellbeing.
What we did: Through the Neighbourhood Effects on Health and Well-Being Study (NEWH), we worked to create a method capable of modeling the complex web of relationships between neighbourhood characteristics and health outcomes, focusing on the City of Toronto. This included:
– Choosing neighbourhoods evenly distributed across Toronto’s geography, and talking to approximately 50 households per neighbourhood. We also took care to make sure that households chosen would, as a whole, reflect the range of populations living in the city.
– Combining a number of data sources (quantitative interviews, census measures, on-line listings of community-based resources) to explore a number of neighbourhood characteristics (socio-economic status, availability of services, litter, community cohesion, etc.).
– Combining a number of data sources (quantitative interviews, health care records) to explore a number of health outcomes (depression, anxiety, body mass index, chronic health conditions, etc.).
What we found: Using this approach, we were able to look at the interactions between neighbourhoods and health from a number of different angles. For example, we found that lack of social cohesion and neighbourhood problems were associated with negative mental health outcomes for women and people over 60. Additional findings and more details related to this method available in full text journal article here.
Several studies have been generated using data from the Neighbourhood Effects on Health and Well-Being Study (NEHW).
– Toronto Public’s Health 2013 report, Racialization and Health Inequities in Toronto, used data generated by project NEHW.
– We explored the association between socio-economic status and dental health.
Upcoming studies will explore associations between neighbourhood and sleep, and neighbourhood and food security.