Environmental phenotypes for healthy weight in children using population-based linked environment and health data: a cross-sectional observational study

BACKGROUND: Childhood obesity is a major global health challenge, projected to affect one in three children worldwide by 2050. While individual and social factors contribute, increasing evidence highlights the built environment as a key determinant in shaping children's behaviours and weight outcomes. Evidence suggests that neighbourhood design, greenspace access, and food retail availability influence diet and physical activity, but most studies rely on small samples or single-domain measures. METHODS: We linked nationwide geographic information systems (GIS) data describing residential neighbourhoods with objectively measured child weight from a national Welsh surveillance programme for children aged 4-5 years. Using multiple indicators-including housing type, garden size, neighbourhood greenness, walkability, access to recreational spaces, and food outlet density - latent class analysis was used to identify distinct "environmental phenotypes." Associations between phenotypes and child weight status were examined using logistic regression. RESULTS: We identified discrete classes of residential environments characterised by varying combinations of built and food environment features. The model with five classes was the best fit overall, with percentage and number of households in each phenotypes: Rural, spacious and isolated 14% (24,266), Suburban 17% (29,324), Deprived and underserved 23% (39,227), Deprived and well-served 32% (53,210), and Dense, coastal and well-connected 13% (21,762). Children living in rural, spacious and isolated neighbourhoods, characterised as those with greater greenspace, private gardens, and walkable layouts, had significantly lower odds of overweight and obesity (OR = 0.89, CI = 0.86-0.93), whereas those in deprived and well-served neighbourhoods, characterised by high-density housing areas with limited greenspace and high fast-food outlet density, had elevated risk (OR = 1.09, CI = 1.06-1.13). These associations remained robust after adjustment for area-level deprivation and rurality. CONCLUSION: Our findings highlight the importance of the residential environment in early childhood obesity risk. Nationally linked GIS and health data enable robust classification of obesogenic environments, informing urban planning and public health strategies to promote healthier, child-friendly neighbourhoods.