Background: Previous research has shown that female adolescents and adults report lower health status than their male peers. Possibly, this discrepancy already develops during childhood. We collected sex-specific data with the Pediatric Quality of Life Inventory (PedsQL) in a large school-based sample.

Methods: The online version of the PedsQL was administered to healthy Dutch children aged 5-7 years (parent proxy-report), 8-12 years (parent proxy-report and child self-report), and 13-17 years (parent proxy-report and child self-report), recruited through regular primary and secondary schools. Sex differences were assessed using t-tests or Mann-Whitney U-tests. Wilcoxon signed-rank tests and intraclass correlation coefficients served to compare parent proxy-reports with child self-reports. Multivariable linear regression analyses were used to assess the associations of sex of the child, age, and parental educational level with PedsQL scores.

Results: Eight hundred eighty-two parents and five hundred eighty one children were recruited from 15 different schools in the Netherlands. Parents of 8-to-12-year-olds reported higher scores on School Functioning for girls than for boys (mean difference [MD]: 6.56, p < 0.001). Parents of 13-to-17-year-olds reported lower scores on Physical and Emotional Functioning for girls than for boys (MDs: 2.14 and 5.79, p = 0.014 and p < 0.001, respectively). Girls aged 8-12 years reported lower scores than boys in this age group on Physical Functioning (MD: 3.09, p = 0.005). Girls aged 13-17 years reported lower scores than boys in this age group on Physical Functioning (MD: 3.67, p < 0.001), Emotional Functioning (MD: 8.11, p < 0.001), and the Total Score (MD 3.26, p = 0.004). No sex differences were found in children aged 5-7 years. Agreement between child self-reports and parent proxy-reports was poor to moderate.

Conclusions: Girls generally had lower PedsQL scores than boys, both in parent proxy-reports and in child self-reports. We recommend to apply sex-specific data when assessing health status using the PedsQL.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8683815PMC
http://dx.doi.org/10.1186/s12887-021-03059-3DOI Listing

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