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. 2017 Jan 12;12(1):e0168186. doi: 10.1371/journal.pone.0168186

Table 3. Quality assessment of the included studies.

Author, year, reference Selection bias Confounding Measurement Study attrition Data analysis Overall quality Comment
High-quality studies
Hallal, 2006[62]
Hallal, 2012[60]
Kehoe, 2002[48]
Medium-quality studies
Atladottir, 2000[28]
Barbieri, 2009[29]
Cardona Cano, 2015 [40]
Gopinath, 2013[14]
Migraine, 2013[42]
Pearce, 2012[51]
Perälä, 2012[33]
Ridgway, 2011[11]
Silveira, 2012[44] Identical study population as Escobar, 2014
Van Deutekom, 2015[54]
Wijtzes, 2013[55]
Low-quality studies
Andersen, 2009[45]
Boone-Heinonen, 2015[30]
Boonstra, 2006[38]
Brown, 2012[39]
Campbell, 2010[46]
Davies, 2006[10]
Dubignon, 1969[31]
Eriksson, 2004[15]
Escobar, 2014[41] Identical study population as Silveira, 2012
Hack, 2012[12]
Hildebrand, 2015[47]
Kajantie, 2010[56] Identical study population as Kaseva, 2012, Kaseva, 2013 and Kaseva, 2015
Kaseva, 2012[13] Identical study population as Kajantie, 2010, Kaseva, 2013 and Kaseva, 2015
Kaseva, 2013[61] Identical study population as Kajantie, 2010, Kaseva, 2012 and Kaseva, 2015
Kaseva, 2015[57] Identical study population as Kajantie, 2010, Kaseva, 2012 and Kaseva, 2013
Laaksonen, 2003[59]
Li, 2015[32]
Mattocks, 2008[49]
Oliveira, 2015[43]
Ounsted, 1975[37]
Pahkala, 2010[50]
Robinson, 2013[36]
Rogers, 2005[58]
Ruiz-Narváez, 2014[34]
Said-Mohamed, 2012[52]
Salbe, 1998[53]
Shultis, 2005[35]

Results of the quality assessment of the included studies, with each dimension judged as strong(●), moderate (◉) or weak (○) based on the judgment rules as defined in Table 1.