tokens: et al. 2009 ; Rosario et al. 2013 , 2016 , 2018 , and references therein) or mid-infrared neon ([Ne ii ] 12.81 μ m and [Ne iii ] 15.56 μ m) emission lines (Zhuang, Ho Shangguan 2019 ). The infrared observations used in these works are obtained using large apertures, including the whole galaxy emission. As discussed in Rosario et al. ( 2016 ), despite finding a good correlation between far-infrared emission and SFR (which can be attributed to leaking of the SF regions to the whole galaxy or that the SF is constant over several hundreds of Myr) a substantial component of the cold dust luminosity that is associated with a diffuse interstellar radiation field can come from evolved stars. Even if the contribution from an old age stellar population is not dominant, the far-infrared may not be a good tracer of SF since dust can be heated by stars that are older than a few hundred Myr (Kennicutt et al. 2009 ; Hao et al. 2011 ; Rosario et al. 2016 ). Other recent effort on the bluer part of the spectrum has been made using a re-calibration [O ii ] λ3727 emission line (Zhuang et al. 2019 ; Zhuang, Ho Shangguan 2020 ), which is metallicity and electron density dependent. From the above, it is clear that it is thus necessary to find an independent way to obtain SFRs in AGN hosts. A powerful technique to disentangle the components summing up to a galaxy spectral energy distribution (SED) is stellar populations synthesis (e.g. Cid Fernandes et al. 2004 , 2005 ; Riffel et al. 2009 , 2008 ; Walcher et al. 2011 ; Baldwin et al. 2018; Cid Fernandes 2018 ; Salim, Boquien Lee 2018 ; Peterken et al. 2020 , and references therein). The synthesis is based on the simultaneous fit of different proportions of composite or simple stellar populations (SSPs) templates from a base of such spectra to the observed spectrum. In the case of the starlight fitting code (Cid Fernandes et al. 2004 , 2005 ; Cid Fernandes 2018 ), it returns the values of the gas mass rate that has been converted into stars throughout the galaxy life as well as this rate for each single SSP included in the base. These values can therefore be used to compute the SFR via stellar population synthesis, SFR ⋆ . In fact, this was already applied in Asari et al. (2007) using single fiber Sloan Digital Sky Survey (SDSS) data and older stellar population models generations (they used Bruzual Charlot 2003 models). From the discussion above, it is clear that it is of utmost importance to characterize the SFR of AGN hosts – in particular in the narrow-line region (NLR) and extended narrow-line region (ENLR), which are photoionized by the AGN. And in order to verify the actual role of the AGN on the SFR, it is necessary to compare the SFR values obtained for the NLR and ENLR with those obtained for a matched control sample of non-active galaxies at similar distances from the nucleus, as well as with predictions from simulations. In Rembold et al. ( 2017 ), we described the method we have used to select
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