Table 3 Results from the papers with specific outcomes and exposures. Direction of qualitative (good vs. poor) association of air pollutants and health indicators designated through up and down arrows. Significant results are denoted by a star and in bold. Dagger indicates association was shown in paper but the direction not reported
Results | |||||||||
|---|---|---|---|---|---|---|---|---|---|
First Author, year | Country | Health Indicators | Pollution/PM | PM2.5 | PM10 | CO | O3 | NOx | SO2 |
Nti, 2020 | Ghana | FEV1, FVC, FEV1/FVC, PEF, FEF25-75 | - | ↓ | ↓ | - | - | - | - |
Hamatui, 2017 | Namibia | Episodes of phlegm and cough | ↑↓ | - | - | - | - | - | - |
Naidoo, 2013 | South Africa | Chronic Bronchitis, Persistent Asthma | - | † | ↓ | - | - | † | ↓ |
Baatjies, 2013 | South Africa | Total hours of exposure, cumulative exposure, peak exposure | - | - | - | - | - | - | ↑↓ |
Olaniyan, 2020 | South Africa | Rhinitis, Asthma, FEV1, FVC, FEV1/FVC, FEF25-75, Change in FEV1,FENO | - | ↑↓ | - | - | - | ↓ * | - |
Zwi, 2020 | South Africa | Rhinitis and Asthma | ↓ * | - | - | - | - | - | - |
Reddy, 2012 | South Africa | 5 day average % change in intraday variability of FEV1 | - | - | ↓ | - | - | ↓ | ↑ |
Makamure, 2016 | South Africa | 5 day average % change in Intraday variability of FEV1, 5 day average of Intraday variability of PEF | - | - | ↓ | - | - | ↓ | ↓ |
Makamure, 2017 | South Africa | 5 day average % change in Intraday variability of FEV1 | - | - | ↓ | - | - | ↓ | ↓ |
Mentz, 2018 | South Africa | Respiratory Symptoms: (cough, wheeze, shortness of breath, chest tightness) | - | † | ↓ * | † | † | ↓ * | ↓ * |
Mentz, 2019 | South Africa | Change in FEV1 | - | - | † | † | † | ↓ * | † |
Mustapha, 2011 | Nigeria | Asthma and Rhinitis | ↑ | ↑↓ | ↑ | ↑ | - | - | - |
Nightingale, 2019 | Malawi | Cough, Phlegm, Wheeze, Dyspnea, Functional Limitation, Any symptom, FEV1, FVC FEV1/FVC | - | ↓ * | - | ↑↓ | - | - | - |
Rylance, 2020 | Malawi | FEV1 and FVC | - | † | - | † | - | - | - |