Background Material, psychosocial and behavioural factors are important explanatory pathways for socioeconomic inequalities in health. The aim of this systematic review was to summarise the available evidence on empirical studies and to analyse the relative contribution of these factors for explaining inequalities in self-rated health. Methods The study was performed in compliance with PRISMA guidelines. The literature search was conducted in the electronic databases PubMed and Web of Science (1996–2016) as well as by screening of reference lists of obtained articles. Two reviewers performed the search and critical appraisal of the studies. All studies that focus on explaining socioeconomic inequalities in self-rated health, including at least 2 of the 3 main pathways and analysing the relative contribution of these approaches in separate and joint models, were included. Results Eleven publications were included. Separate analyses showed that material, psychosocial and behavioural factors contribute to the explanation of socioeconomic inequalities in self-rated health. However, the combined analyses revealed that material factors contributed most to differences in self-rated health because of their higher independent (direct) effect and additional shared (indirect) effect (through psychosocial and behavioural factors). These results were largely independent of age, gender and indicator of socioeconomic status. Conclusions The evidence presented might be used for policymakers to identify and to justify prioritisation in terms of prevention and health promotion. The findings show that multiple factors are important for tackling social inequalities in health. Strategies for reducing these inequalities should focus on material/structural living conditions as they shape conditions of psychosocial resources and health behaviour.

Background: Tobacco-related heath inequalities are a major public health concern, with smoking being more prevalent among lower socioeconomic groups. The aim of this study is to investigate the mechanisms leading to socioeconomic inequalities in smoking among 15-year-old adolescents by examining the mediating role of psychosocial factors in the peer group, family and school environment. Methods: Data were derived from the international WHO-collaborative ‘Health Behaviour in School-aged Children (HBSC)’ study 2005/2006, including 52 907 15-year-old students from 35 European and North American countries. Socioeconomic position was measured by the Family Affluence Scale. Multilevel logistic regression models were conducted to examine the contribution of family, school and peer factors in explaining the association between family affluence and weekly smoking. Results: Across countries, adolescents from low affluent families had an increased risk of weekly smoking (ORboys 1.14, confidence interval (CI) 1.05–1.23; ORgirls 1.36, CI 1.26–1.46) compared with adolescents from high affluent families. Family and school factors mediated the association between family affluence and smoking to a high extent up to 100% (boys) and 81% (girls) in joint analyses. The most important single factors were family structure, relationships with parents, academic achievement and school satisfaction. Peer factors did not mediate the association between family affluence and adolescent smoking. Conclusion: The association between socioeconomic status and adolescent weekly smoking can largely be explained by an unequal distribution of family- and school-related factors. Focusing on the parent–adolescent relationship and adolescent school achievement can help to better understand inequalities in adolescent smoking behaviour.

Adolescence is a critical period where many patterns of health and health behaviour are formed. The objective of this study was to investigate cross-national variation in the relationship between family affluence and adolescent life satisfaction, and the impact of national income and income inequality on this relationship. Data from the 2006 Health Behaviour in School-aged Children: WHO collaborative Study (N = 58,352 across 35 countries) were analysed using multilevel linear and logistic regression analyses for outcome measures life satisfaction score and binary high/low life satisfaction. National income and income inequality were associated with aggregated life satisfaction score and prevalence of high life satisfaction. Within-country socioeconomic inequalities in life satisfaction existed even after adjustment for family structure. This relationship was curvilinear and varied cross-nationally. Socioeconomic inequalities were greatest in poor countries and in countries with unequal income distribution. GDP (PPP US$) and Gini did not explain between country variance in socioeconomic inequalities in life satisfaction. The existence of, and variation in, within-country socioeconomic inequalities in adolescent life satisfaction highlights the importance of identifying and addressing mediating factors during this life stage.