Table 1.
Features of the studies imported to the meta-analysis
| No | Author/ publication year | Country | City | Design | Study period (month) | Lag exposure | Case population (n) | Adjustment | Quality score |
|---|---|---|---|---|---|---|---|---|---|
| 1 | (Peters et al., 2001) [28] | USA | Boston | Case-Crossover | 5 | Lag0 | 772 | Day of the week, season, and meteorological parameters on the same time scales | High |
| 2 | (Peters et al., 2005) [29] | Germany | Augsburg | Case -Crossover | 24 | Lag0, Lag5, Lag0–4 | 851 | Temperature, humidity, days of the week, pressure | High |
| 3 | (Sullivan et al., 2005) [30] | USA | Washington | Case-Crossover | 72 | Lag0 | 5793 | Relative humidity and temperature | High |
| 4 | (Pop et al., 2006) [31] | USA | Utah | Case-Crossover | 120 | Lag0, Lag3 | 3910 | Temperature | Low |
| 5 |
(Zanobetti &Schwartz et al. 2006) [32] |
USA | Boston | Time Series | 48 | Lag0, Lag0–1 | 15,578 | Temperature, days of the week | High |
| 6 | (Barnett et al., 2006) [33] | Australia | Auckland, Brisbane, Canberra, Christchurch, Melbourne, Perth, Sydney | Case-Crossover | 36 | Lag0–1 | 56,036 | Day of week, pressure, holidays, temperature, humidity and others | High |
| 7 | (Ueda et al., 2009) [34] | Japanese | Fukuoka, Kawasaki, Kobe, Nagoya, Osaka, Sapporo, Sakai, Sendai and Tokyo | Time Series | 24 | Lag0, Lag1 | 67,897 | Days of the week, seasonality, relative humidity, ambient, and temperature | Low |
| 8 | (Stieb et al., 2009) [35] | Canada | Edmonton, Halifax, Montreal, Ottawa, Saint John, Vancouver and Toronto | Time Series | 120 | Lag0, Lag1, Lag2 | 63,184 | Seasonal cycles, temperature, and humidity | High |
| 9 | (Belleudi et al., 2010) [36] | Italy | Rome | Case-Crossover | 56 | Lag0, Lag6 | 7520 | Influenza, population reduction, epidemics, pressure, and Temperature | Low |
| 10 | (Zanobetti &Schwartz 2009) [37] | USA | 112 cities (The biggest cities are California, New York City, Los Angeles, Chicago, Illinois and New York) | Time Series | 72 | Lag0–1 | 397,894 | Long-term trend, seasonality, temperature, days of the week | High |
| 11 | (Rich et al., 2010) [38] | USA | New Jersey | Case-Crossover | 24 | Lag0 | 5864 | Weather and days of the week | High |
| 12 | (Berglind et al., 2010)a [39] | Sweden | Boston | Case-Crossover | 24 | Lag0 | 772 | Relative humidity and temperature | Low |
| 13 | (Berglind et al., 2010) b [39] | Sweden | Seattle | Case-Crossover | 24 | Lag0 | 5793 | Relative humidity and temperature | Low |
| 14 | (Berglind et al., 2010) c [39] | Sweden | Augsburg | Case-Crossover | 24 | Lag0 | 691 | Temperature and relative humidity | Low |
| 15 | (Mate et al., 2010) [40] | Spain | Madrid | Time Series | 24 | Lag6 | 1096 | Days of the week, trend, seasonality, influenza and temperature | High |
| 16 | (von Klot et al., 2011) [41] | Germany | Augsburg | Case-Crossover | 48 | Lag0 | 960 | Days of the week and temperature | High |
| 17 | (Chang et al., 2013) [42] | Taiwan | Taipei | Case-Crossover | 48 | Lag0 | 14,353 | Temperature and relative humidity | High |
| 18 | (Rosenthal et al., 2013) [43] | Finland | Helsinki | Case-Crossover | 96 | Lag0, Lag1, Lag2, Lag3,Lag0–3 | 629 | Temperature and humidity | High |
| 19 | (Talbott et al., 2014) [21] | USA | Florida | Case-Crossover | 96 | Lag0, Lag1, Lag2, Lag0–2 | 135,421 | Maximum apparent temperature and ozone | Low |
| 20 | (Gardner et al., 2014) [44] | USA | New York | Case-Crossover | 36 | Lag0–1,Lag0–2, Lag0–3, Lag0–4 | 677 | Relative humidity and temperature | High |
| 21 | (Milojevic et al., 2014) [45] | UK | London | Case-Crossover | 72 | Lag0–4 | 452,343 | Temperature, days of the week | High |
| 22 | (Wichmann et al., 2014) [46] | Sweden | Gothenburg | Case-Crossover | 300 | Lag0, Lag1, Lag0–1 | 28,215 | Relative humidity, temperature and public holiday | High |
| 23 | (Wang et al., 2015) [47] | Canada | Calgary, Edmonton | Case-Crossover | 132 | Lag(0,1.2.3,4) | 22,628 | daily average of temperature, dew point temperature and wind speed | Low |
| 24 | (Zang et al., 2016) [48] | China | Chaoyang | Case-Crossover | 12 | Lag(0,1,2,3,4,5) | 2749 | meteorological conditions and/or other gaseous pollutants | High |
| 25 | (Argacha et al., 2016) [49] | Belgian | Belgian | Case-Crossover | 48 | Lag0 | 11,428 | Day of the week, temperature | High |
| 26 | (Baneras et al., 2017) [20] | Spain | Barcelona | Time Series | 24 | Lag0 | 4141 | Seasonal, meteorological factors, and time-calendar variables | High |
| 27 | (Akbarzadeh et al., 2018) [50] | Iran | Tehran | Case-Crossover | 24 | Lag0–1 | 208 | Temperature and humidity | Low |
| 28 | (Yu et al., 2018) [51] | China | Changzhou | Time Series | 24 | Lag(0,1,2,3,4,5,6), Lag(0–1,0-2,0-3,0-4,0-5,0–6) | 5545 | Temperature, days of the week, relative humidity, seasonal trends | Low |