Objective  To construct an integrated index of family socioeconomic gradient for providing a valid assessment of socioeconomic status (SES) of the mother and her child/children in a family.

  Methods  The participants of the study were 16 175 pregnant women and their children enrolled between February 2012 and June 2016 from the Birth Cohort Study in Guangzhou. Information on social and economic condition of the children′s parents were collected. Principal components analysis (PCA) and standard score (Z-score) summative method were used to construct a family SES score. The consistency among different combinations of socioeconomic variables in the evaluation on families′ socio-economic gradient were compared.

  Results  Significant pairwise correlations were observed among 9 parental socioeconomic variables (maternal education, paternal education, average maternal monthly income, average paternal monthly income, maternal employment, family real estate ownership, private car ownership, per capita living space, and residential floor), except for the associations of maternal employment with per capita living space and residential floor; the coefficients for the correlations ranged from – 0.036 to 0.585 (P < 0.01 for all). The SES grouping of the pregnant women by the integrated index established using PCA method on account of the nine variables was consistent well with that using Z-score summative method, with a weighted Kappa coefficient of 0.737 (95% confidence interval 95% CI: 0.730 – 0.743); both of the indexes could accurately reflect the mothers′ and children′s family socioeconomic gradients. An integrated index established using the Z-score summative method based on 8 parental socioeconomic variables showed the best consistence with that using PCA method on account of the 9 parental socioeconomic variables, with a weighted Kappa coefficient of 0.774 (95% CI: 0.768 – 0.780).

  Conclusion  The integrated index established in the study using PCA method and Z-score summative method based on 9 parental socioeconomic variables could be used to conduct valid assessment on family socioeconomic gradients of Chinese women and children.