Back

Neighbourhood food environments in the Southeast Asian context: Profiling energy density and macronutrient exposure with overweightness in 15,614 adults in Singapore

Ma, P.; Chew, Y. Z.; Song, H.; Chong, M. F.-F.; Mueller-Riemenschneider, F.; Jin, S.; Dickens, B. L.

2025-04-11 public and global health
10.1101/2025.04.10.25325565 medRxiv
Show abstract

Rising overweight prevalence in Southeast Asian urban settings is contributing to substantial chronic disease burdens. The role of fast food outlet density or broader macronutrient-based exposure in these settings, as well as the applicability of international food environment measures, remains underexplored. Using Singapore as a case study representative of dense Southeast Asian cities such as Bangkok, Manila, Jakarta, Ho Chi Minh City, and Kuala Lumpur, we examine geospatial correlations between macronutrient exposure and overweightness rather than relying on categorical food outlet classifications. Data from 15,614 participants in Singapores Multi-ethnic Cohort were used to estimate macronutrient-based profiles of 14,764 geolocated food establishments and built environment covariates across 234 zones. Bayesian hierarchical models indicated that higher saturated fat exposure was associated with increased overweight risk (adjusted odds ratio [AOR] 1.11, 95% CrI 1.03-1.26), while greater exposure to green space was associated with reduced risk (AOR 0.65, 95% CrI 0.49-0.78). When we adjusted for multilevel spatial dependence, high saturated fat score remained significant. The association between overweight status and fast food outlet density was not statistically significant (AOR 1.00, 95% CrI 0.95-1.04). These findings suggest that spatial variation in nutritional exposure is associated with overweight risk beyond measures of fast food outlet density in Singapore, highlighting the need for more tailored and region specific urban planning approaches that consider the macronutrient landscape across similar cities in the wider region, potentially focusing on the availability of saturated fat in the local food environment.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.