The physicochemical and biological indices have been used in isolation; if the parameters of these indices were applied in an integrated manner, they would bring together in a single measure the functional and structural variability of the biotic and abiotic components of water quality. The aim of this study was to build a comprehensive water quality index. Eleven sampling points were selected considering different degrees of agro-industrial intervention. 21 abiotic variables and 27 biological metrics were measured. Macroinvertebrates were quantitatively collected and identified to family taxonomic level. Using Principal Component Analysis, after standardization and exclusion of uncorrelated variables (VIF ≤ 10), the abiotic gradient was determined, which represented the abiotic variables that explained the disturbances in the water; with the abiotic gradient and the biological metrics, a Pearson correlation was performed, and those biological metrics that presented a high and non-redundant correlation were selected (Pearson 0.6 ≤ r ≤ 0.8); with the selected biological metrics, we proceeded to formulate and categorize the index; finally, by means of simple linear regression, the proposed index was compared with five other indexes (ICA, ICOMO, EPT, BMWP/col. and ASPT). The results showed that the abiotic gradient was defined by CP 1 which explained 65.5% of the accumulated variance, represented by altitude (r = 0.411), iron (r = 0.345) and dissolved oxygen (r = 0.329). The biological metrics used for the index design were: % scrapers, % swimmers, NEF of order 2, Ephemeroptera and Trichoptera tolerance. It was concluded that the integral index presents a higher predictive level (R2 = 0.87) of water quality, compared to the other indices: ASPT (R2 = 0.79), BMWP/col. (R2 = 0.68), EPT (R2 = 0.61), ICOMO (R2 = 0.35) and ICA (R2 = 0.27).