Accelerating progress towards the sustainable development goals for adolescents in Ghana: a cross-sectional study

Abstract

ABSTRACT Since the adoption of the sustainable development goals (SDGs) by the United Nations (UN), the search has been on to identify interventions that have effects on multiple SDG-targets simultaneously. Like other developing countries, Ghana has a youthful population and would require creative, urgent, youth-focused interventions to be able to attain the SDGs by 2030. This paper describes the application of the accelerator model on data from a sample of Ghanaian adolescents to identify potential accelerators towards selected SDG targets involving youth. The data for 944 adolescents, 10–19 years (mean age 12.31 ± 3.51 years), extracted from two cross-sectional surveys on children and adolescents aged 6–19 years in Kumasi, Ghana, were analysed in this paper. Variables considered suitable proxies for SDG targets and potential accelerators were identified from the study instruments. Consequently, four aligned SDG targets (good mental health, access to ICT, school completion and no open defaecation) and five accelerators (cognitive stimulation, no relative poverty, low student–teacher ratio, high caregiver education and safe water) were extracted. Associations between accelerators and SDG targets were assessed using multivariable logistic regression adjusting for sociodemographic covariates and multiple testing. Cumulative effects were tested by marginal effects modelling. The three hypothesised accelerators identified were cognitive stimulation, low student–teacher ratio, and no relative poverty. A combination of all three accelerators was associated with a higher likelihood of adolescents having access to Information and Communication Technology (ICT) by +73% (CI 0.72–0.74), no open defecation by +44% (CI 0.43–0.46), school completion by +27% (CI 0.26–0.27) and good mental health by +9% (CI 0.08–0.10). Three hypothesized accelerators showed association across all four SDG aligned targets. The accelerator model has been further validated in this dataset from Ghana. Robust interventions designed around these accelerators may represent an opportunity for achieving the SDGs in Ghana.