Mortality inequalities by environment type in New Zealand

Mental Health Outcome Measures in Environmental Design Research: A Critical Review

AIM

During the last several decades, researchers have produced abundant evidence of the environmental impacts on stress, attention, and physical activity. More recently, scholars have turned their focus to the influence environments have on mental wellness. Therefore, a critical review of this more recent research is both timely and crucial for setting the future research agenda.

METHODS

In this article, we examined 65 papers published between 2008 and 2019 that examined the environmental correlates of a wide variety of mental health outcomes. We coded each study by type of environment, research design, mental health measurement scale used, and p-value.

RESULTS

We categorized the research studies into six groups based on mental health outcomes: emotions, moods, vitality, executive function, stress, and general well-being. Our review revealed several trends among the studies, including a heavy focus on nature and outdoor environments with little attention to workplace or residential environments; a lack of consensus on how to operationalize the environment; a heavy reliance on self-reported ratings using a wide variety of scales, many focused on the same outcome; and a disproportionate focus on short-term health effects.

CONCLUSIONS

There is a need for greater consensus on research constructs and health outcome measurements, focused on a wider variety of environmental settings and scales, in order to better inform evidence-based environmental design practice.

Premature mortality resilience and wellbeing within urban Māori communities

Māori (the indigenous peoples of Aotearoa New Zealand) experience of colonisation has negatively affected access to many of the resources (e.g. income, adequate housing) that enable health and well-being. However Māori have actively responded to the challenges they have faced. With the majority of the Māori population now living in urban settings this exploratory study aimed to understand factors contributing to mortality resilience despite exposure to socio-economic adversity with reference to Māori well-being. Resilient urban neighborhoods were defined as those that had lower than expected premature mortality among Māori residents despite high levels of socio-economic adversity. Selected resilience indicators theoretically linked to a Māori well-being framework were correlated with the novel Māori_RINZ resilience index. Of the selected indicators, only exposure to crime showed a clear gradient across the resilience index as predicted by the Māori well-being framework. Future research is needed as unclear trends for other indicators may reflect limitations in the indicators used or the need to develop a more comprehensive measure of well-being.

Data analysis techniques: a tool for cumulative exposure assessment

Everyone is subject to environmental exposures from various sources, with negative health impacts (air, water and soil contamination, noise, etc.or with positive effects (e.g. green space). Studies considering such complex environmental settings in a global manner are rare. We propose to use statistical factor and cluster analyses to create a composite exposure index with a data-driven approach, in view to assess the environmental burden experienced by populations. We illustrate this approach in a large French metropolitan area. The study was carried out in the Great Lyon area (France, 1.2 M inhabitants) at the census Block Group (BG) scale. We used as environmental indicators ambient air NO2 annual concentrations, noise levels and proximity to green spaces, to industrial plants, to polluted sites and to road traffic. They were synthesized using Multiple Factor Analysis (MFA), a data-driven technique without a priori modeling, followed by a Hierarchical Clustering to create BG classes. The first components of the MFA explained, respectively, 30, 14, 11 and 9% of the total variance. Clustering in five classes group: (1) a particular type of large BGs without population; (2) BGs of green residential areas, with less negative exposures than average; (3) BGs of residential areas near midtown; (4) BGs close to industries; and (5) midtown urban BGs, with higher negative exposures than average and less green spaces. Other numbers of classes were tested in order to assess a variety of clustering. We present an approach using statistical factor and cluster analyses techniques, which seem overlooked to assess cumulative exposure in complex environmental settings. Although it cannot be applied directly for risk or health effect assessment, the resulting index can help to identify hot spots of cumulative exposure, to prioritize urban policies or to compare the environmental burden across study areas in an epidemiological framework.