Income and asthma-related outcomes in children: a longitudinal study in the United Kingdom

There is evidence that children from socially disadvantaged families tend to have poorer health outcomes than their richer counterparts. However, evidence on the association between family income and specific outcomes, such as asthma and wheezing, is limited. This thesis therefore applies different methodological approaches to investigate the relationship between family income and asthma-related outcomes in children, in the United Kingdom. Chapter 1 presents the motivation and background to the thesis, and Chapter 2 describes the data and gives an overview of the methods used. Three asthma-related outcomes were used, as derived from the Millennium Cohort Study. These were: ever asthma, wheezing in the last 12 months and asthma medication use. Chapter 3 examines cross-sectionally, the association between family income and asthma-related outcomes. The results showed that income is a statistically significant driver of asthma-related outcomes, after taking into account potential confounding factors. Furthermore, for outcomes ever asthma and asthma medication use, there was some evidence that the child health-income gradient strengthened with age, novel findings in the United Kingdom. Chapter 4 considers heterogeneity in asthma-related outcomes in children, and constructed four phenotypes based on the duration and onset of wheezing. Multinomial regression models were fitted to analyse the association between income and wheezing phenotype. Results showed statistically significant associations between income and the late-onset and persistent wheezing phenotypes, which are both likely to persist into adult life. In Chapter 5, empirical methods are used to exploit the longitudinal nature of the data. Two approaches were used: firstly, panel data methods, where fixed and random effects models were fitted to the data. Income effects were statistically weak across all asthma-related outcomes. Secondly, a single regression model was fitted on the combined data across all age groups for each outcome, including an interaction term between income and survey age. Results showed that higher income decreased the probability of asthma-related outcomes. Chapter 6 examines income-related inequity of asthma-related outcomes. The first part of the analysis used Erreygers’ Indices to estimate income-related inequality. Negative indices indicated income-related inequality for all ages and outcomes. Income-related inequality was then decomposed into contributing factors, and showed that income itself is the main driver. Overall, the findings show that children from low-income families are at higher risk of adverse asthma-related outcomes, and that the burden of asthma-related disease is more concentrated in low-income children. In light of this, policies should therefore focus on reducing the degree of income-related inequality in asthma outcomes in children, by tackling the key drivers of inequality.