Characterising residential mobility during childhood in the United Kingdom: a longitudinal study using linked electronic health records - Nicola Firman; Laura North; Jane Lyons; Marta Wilk; Michael Edwards; Rhodri D. Johnson; Rowena Bailey; Jo Davies; Gill Harper; Carol Dezateux; Richard Fry; Lucy J. Griffiths (Longitudinal and Life Course Studies, 2026)
Background: Childhood residential mobility (RM) has been associated with adverse health and social outcomes. We examined differences in RM by family size and household composition in two diverse, disadvantaged UK populations. Methods: Using electronic health records (EHRs) and anonymised addresses, we examined if household characteristics are associated with RM in north-east London (NEL) and Wales. We conducted a longitudinal study of 240,509 (51.0 per cent male) and 398,959 (51.3 per cent male) children aged 0–13 years in NEL and Wales respectively on 1 January 2015, with complete follow-up until 31 December 2019. We defined RM as at least one change in address during follow-up. We estimated odds ratios (OR) and 95 per cent confidence intervals (CI) for RM by interactions between age group (0–4, 5–9, 10–13 years), number of children in household and household composition, adjusting for demographic, household and area-level characteristics. Results: Overall, 20.6 per cent and 32.1 per cent of children experienced RM. RM was highest in the youngest age group: NEL: 25.3 per cent, 18.7 per cent, 15.6 per cent; Wales: 40.1 per cent, 29.4 per cent, 23.6 per cent. RM was more likely among 10–13-year-olds living with a single adult than two working-age adults (NEL OR: 1.15; 95 per cent CI: 1.07,1.25; Wales: 1.82; 1.73,1.91). Children in households with four or more children were more likely to experience RM than those with no other child among 10–13-year-olds in NEL (1.31; 1.18,1.46) and 5–9-year-olds and 10–13-year-olds in Wales (1.21; 1.14,1.29 and 1.68; 1.56,1.82). Conclusion: RM is more common in early childhood and varies by household composition, region and age group. EHRs can be used to estimate RM using real-world data and have the potential to examine its impact on health and other outcomes.