(AQ4LC)
It is well documented within academia and the general media of the increasing risks associated with poor environmental air quality levels. Numerous studies, including a 2013 assessment of Chinese cities discovered that only 4.1% of the 74 cities monitored, met official air pollution standards in terms of PM2.5, with an annual average PM2.5 value of 72 μg/m3 (Guo et al., 2016). In developing countries there is even a higher burden of indoor air pollution as a high number of biomass stoves are used indoors for cooking (Gupta, 2019)(Smith, 2002). Indoor air pollution increases the risk to upper respiratory tract infections. Studies have shown chronic exposure to biomass smoke-generated indoors can cause a wide range of health effects such as chronic obstructive pulmonary disease (COPD) (Sehgal, Rizwan and Krishnan, 2014)(Neidell, 2004). Asthma is one of the upper respiratory conditions that affect individuals as a result of poor air quality.
When it comes to air quality monitoring and asthma self-management, there are a number of new technologies coming to the market, including, the utilisation of a network of handheld air quality monitors (Dutta et al., 2009) to environment crowd-sensing for asthma management (Vasilateanu, Radu and Buga, 2016) and (Tinschert et al., 2017) on mobile apps for Asthma self-management to the installation of air particle monitors to provide digital coaching to reduce indoor smoking (Hovell et al., 2020). Such technologies combined have the potential to offer greater levels of asthma self-management which may result in a higher standard of living.
Finally, “adequate asthma management depends on an accurate identification of asthma triggers. A review of the literature on trigger perception in asthma shows that individuals vary in their perception of asthma triggers and that the correlation between self-reported asthma triggers and allergy tests is only modest.” (Janssens and Ritz, 2013). Within the Air for LIFE Consortium our initial trial will be looking to assess the impact of using personalised air quality monitors as part of Asthma self-management in both urban and rural settings in Malawi, Africa.
Team members:
Adina Elena Zagoneanu,
Sydney Brannen,
Tarun Das,
Dr Trevor Nichols,
Dr Oisin O’Connell,
Dr Patrick Henn,
Simeon Yosefe,
Hsin-yi Lee,
Joseph Wu,
Prof. Chang-Chuan Chan,
Prof. Sally Chen,
Prof. Richard Costello,
Prof. Joe Gallagher,
Hastings Gondwe,
Dr Griphin Baxter Chirambo,
Dr John O’Donoghue.
References:
Dutta, P. et al. (2009) ‘Demo abstract: Common sense - Participatory urban sensing using a network of handheld air quality monitors’, Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, SenSys 2009, pp. 349–350. doi: 10.1145/1644038.1644095.
Guo, Y. et al. (2016) ‘Factors affecting parent’s perception on air quality-from the individual to the community level’, International Journal of Environmental Research and Public Health, 13(5). doi: 10.3390/ijerph13050493.
Gupta, A. (2019) ‘Where there is smoke: solid fuel externalities, gender, and adult respiratory health in India’, Population and Environment. Springer Netherlands, 41(1), pp. 32–51. doi: 10.1007/s11111-019-00325-6.
Hovell, M. F. et al. (2020) ‘Randomised controlled trial of real-time feedback and brief coaching to reduce indoor smoking’, Tobacco Control, 29(2), pp. 183–190. doi: 10.1136/tobaccocontrol-2018-054717.
Janssens, T. and Ritz, T. (2013) ‘Perceived triggers of asthma: Key to symptom perception and management’, Clinical and Experimental Allergy, 43(9), pp. 1000–1008. doi: 10.1111/cea.12138.
Neidell, M. J. (2004) ‘Air pollution, health, and socio-economic status: The effect of outdoor air quality on childhood asthma’, Journal of Health Economics. North-Holland, 23(6), pp. 1209–1236. doi: 10.1016/j.jhealeco.2004.05.002.
Sehgal, M., Rizwan, S. A. and Krishnan, A. (2014) ‘Disease burden due to biomass cooking-fuel-related household air pollution among women in India’, Global Health Action. Co-Action Publishing, 7(1), p. 25326. doi: 10.3402/gha.v7.25326.
Smith, K. R. (2002) ‘Indoor air pollution in developing countries: Recommendations for research’, Indoor Air. Blackwell Munksgaard, 12(3), pp. 198–207. doi: 10.1034/j.1600-0668.2002.01137.x.
Tinschert, P. et al. (2017) ‘The Potential of Mobile Apps for Improving Asthma Self-Management: A Review of Publicly Available and Well-Adopted Asthma Apps’, JMIR mHealth and uHealth, 5(8), p. e113. doi: 10.2196/mhealth.7177.
Vasilateanu, A., Radu, I. C. and Buga, A. (2016) ‘Environment crowd-sensing for asthma management’, 2015 E-Health and Bioengineering Conference, EHB 2015. IEEE, pp. 1–4. doi: 10.1109/EHB.2015.7391363.