Identifying co-occurring neighbourhood environmental patterns and their association with health behaviours in a Dutch urban population at high cardiometabolic risk
摘要
Pattern-based approaches to characterising neighbourhood environments have been applied across cities and regions, but it is less clear whether they can identify independent environmental effects within a single dense urban area, the scale at which most local public-health interventions are designed. Furthermore, research has primarily focused on general populations, leaving a gap in understanding how environmental factors relate to health behaviours in high-risk groups. This study aimed to (1) describe how a broad set of food-environment, green-space and walkability indicators co-occur in a highly urbanised Dutch city and how the resulting patterns relate to population density and neighbourhood socioeconomic position; and (2) explore whether these patterns are associated with weight status, diet quality and physical activity in primary-care patients at high cardiovascular risk.
MethodsThis cross-sectional study used baseline data from the Healthy Heart study in The Hague, Netherlands (N = 475 participants from 73 postal codes). Twenty-three indicators across food environment, green space and walkability domains were assessed at two spatial scales. Correlation analyses examined intercorrelations among indicators and contextual characteristics. Neighbourhood patterns were identified using principal component analysis (PCA). Associations of component scores with weight status, diet quality and physical activity were examined using (multinomial) logistic and linear regression, adjusted for individual and neighbourhood-level covariates.
ResultsFour components explained 87% of the variance in the environmental indicators. The dominant neighbourhood pattern, characterised by high food-retail density, high walkability and low vegetation cover, correlated very strongly with population density and this coupling persisted within the most highly urbanised stratum. The “Relative food environment advantage” pattern showed the most consistent association across models with lower odds of being overweight, but also counterintuitively with lower fruit and vegetable diet quality. There was some indication of effect modification by neighbourhood socioeconomic position for this pattern.
ConclusionsWithin a single dense urban area, neighbourhood characteristics cluster into structured patterns in urban settings. Food environment measures remained coupled to population density even within high-density areas, fundamentally challenging independent effect estimation. Modest, paradoxical associations suggest limited environmental influence on lifestyle behaviours and weight in medically supervised high-risk populations.