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• We develop a unique dataset of 3 SDG indicators at district level in Lao PDR. • We find a positive correlation between poverty and stunting in 2005 and in 2015. • We find a negative correlation between these indicators and natural areas. • There are no significant relations between changes in indicators over time. • Variations between districts highlight the need for subnational analyses of SDGs. Monitoring the status and evolution of Sustainable Development Goals (SDGs) is typically carried out at the national level. However, significant variation can exist within countries, and this may not be captured by aggregate statistics. Here, we develop a unique dataset representing indicators for three SDGs at a district level for Lao PDR. The indicators comprise prevalence of stunting (SDG 2, Zero hunger), poverty headcount (SDG 1, No Poverty), and share of natural area (SDG 15, Life on land) for two moments in time: 2005 and 2015. In both years, we find considerable variation among district-level outcomes for stunting and poverty. We also find that higher stunting and poverty rates are significantly correlated with higher shares of natural land in both years. This is consistent with the common perception of a trade-off between environmental outcomes and socioeconomic wellbeing. The correlation vanishes, however, when we consider changes in poverty, stunting, and natural area over the ten-year study period. This holds as well when we focus on agricultural land instead of natural areas. We observe that most regions show improvements in both stunting and poverty, albeit not always in a statistically significant sense. This points to synergistic development. Similarly, improvements in both indicators are associated with losses in natural areas in all regions, indicating a trade-off. These results suggest that both trade-offs and synergies between SDGs can arise at the district level, but that context and local conditions likely moderate the strength of these interactions. Our results highlight the importance of quantifying and monitoring sustainable development at the detailed subnational level. [ABSTRACT FROM AUTHOR]