Public engagement with air quality data: using health behaviour change theory to support exposure-minimising behaviours

Abstract

Exposure to air pollution prematurely kills 7 million people globally every year. Policy measures designed to reduce emissions of pollutants, improve ambient air and consequently reduce health impacts, can be effective, but are generally slow to generate change. Individual actions can therefore supplement policy measures and more immediately reduce people's exposure to air pollution. Air quality indices (AQI) are used globally (though not universally) to translate complex air quality data into a single unitless metric, which can be paired with advice to encourage behaviour change. Here we explore, with reference to health behaviour theories, why these are frequently insufficient to instigate individual change. We examine the health behaviour theoretical steps linking air quality data with reduced air pollution exposure and (consequently) improved public health, arguing that a combination of more 'personalised' air quality data and greater public engagement with these data will together better support individual action. Based on this, we present a novel framework, which, when used to shape air quality interventions, has the potential to yield more effective and sustainable interventions to reduce individual exposures and thus reduce the global public health burden of air pollution.

Keywords: Air pollution; Health studies; Behaviour change; Personal exposure.

Fig. 1. A multistage process to improve air pollution-related health.

For air quality data to influence exposure reduction for improved public health requires a multistage process comprising of external (purple) and internal (green) factors. Internal factors are integrated into the process through (adapted) Protection Motivation Theory (PMT; boxes 3a, 3b and 4) and a section of the Health Action Process Approach (HAPA; boxes 5a, 5b and 6).

Fig. 2. Air Quality Indices.

Examples of the information available as part of various AQI including the EU CAQI (A), UK DAQI (B) and US AQI (C).

Fig. 3. A framework to better support behaviour change.

The expanded approach to promote individual behaviour change relies simultaneously on more personally representative data and increased citizen participation moving away from passive participatory processes towards interactive participation (Pretty, 1995). Participation for material incentives has been omitted from the y-axis because it does not generally fit within participatory methods used for behaviour change. Self-mobilisation goes beyond engagement towards empowerment and so is outwith the scope of participatory mechanisms.

Fig. 4. Comparing the ‘traditional’ and ‘expanded’ approach to ultimately improve air pollution-related health.

Left: the traditional approach to promoting exposure minimising behaviours is based on top-down dissemination using highly accurate data with limited personal representativeness. Right: an alternative (‘expanded approach’) approach to supporting exposure minimising behaviours could be more inclusive and collaborative with dialogue between all stakeholders and making use of more interactive data collection methods increasing personal representativeness. Note, both types of appraisal and planning exist in either side of the figure.