Background Evidence on health inequalities is mostly collected on younger children and adults; therefore, socio-economic predictors of adolescent health are not well understood. Physical morbidity is not common among adolescents and young people (YP); however, many chronic health conditions are initiated in those life stages. This project includes four inter-related studies that will improve the understanding of the relationship between socioeconomic factors and self-reported health (SRH) at ages 10-24.

Methods First, we analysed the 2001, 2011 and 2021 Census microdata from England and Wales; and 2001 and 2011 data from Scotland. We applied bivariate and logistic regression analysis to examine SRH status by the family reference person’s socioeconomic status (NS-SEC); controlled for gender, age, household deprivation, and region. Second, we searched four databases for the systematic review that focused on the YPs conceptualisation of health. We used the Quality Framework to appraise included studies and thematic synthesis to develop analytical themes. The third study utilises data from the Scottish Longitudinal Study (SLS) to examine the change in SRH status from 2001 to 2011. The fourth study will link SLS data to administrative prescribing data to analyse the relationship between SRH status and the uptake of prescription medicines.

Results The analysis of Census microdata demonstrated that compared to the higher managerial and professional group, YP from other NS-SEC groups (except the lower supervisory group in 2001), had higher odds of reporting poor health. These differences are statistically significant (p<0.001). The odds were highest among YP from never worked or long-term unemployed households: 2.4 times in 2001, 3.1 times in 2011 and 3.5 times in 2021. The systematic review found that YP consider physical factors when they respond to SRH questions. However, overall, they have a holistic conceptualisation of health. These findings are captured in two analytical themes: 1) Dimensions of health, and 2) Health in context. The analysis of the SLS data is in progress.

Conclusion Analysis of the Census microdata shows that socioeconomic patterning of SRH is evident among YP; we hypothesise that this will also be visible in the change in SRH status over time and in the uptake of prescription medicines. Based on the results of the systematic review we could presume that this reflects differences in health behaviours, and how YP and members of their households perceive their health-related life chances.