Geospatial clustering of type 1 diabetes in Sweden: a cohort study based on all residential locations from birth to diagnosis

瑞典1型糖尿病的地理空间聚集性:一项基于从出生到确诊所有居住地点的队列研究

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Abstract

AIMS/HYPOTHESIS: Type 1 diabetes develops gradually, and previous exposures may influence incidence. We aimed to assess the geographical variation in type 1 diabetes incidence in Sweden by considering all residential locations from birth to diagnosis in individuals aged 0-30 years, diagnosed between 2005 and 2022. Significant high- and low-risk clusters were identified for different life stage exposure windows. METHODS: In 21,774 individuals with type 1 diabetes, all residential geographical locations from birth to diagnosis were geocoded. Geostatistical analysis of the incidence of type 1 diabetes was conducted at the municipality level using the most common residential location during four life stage-specific exposure windows (at diagnosis, the first 5 years after birth, 5 years prior to diagnosis, and from birth to diagnosis). Spatial scan statistics were used to identify statistically significant high- and low-risk clusters for each window. Land use and land cover within these clusters were also characterised. RESULTS: Significant geographical variation in the incidence of type 1 diabetes was observed. The incidence was consistently higher in rural, low-population-density areas, particularly in central Sweden, and lower in major urban areas. The largest number of spatial clusters of both high risk (RR 1.29-16.0) and low risk (RR 0.32-0.73) was identified when using the most common residential location during the first 5 years after birth. High-risk clusters for this exposure window were characterised by forested and agricultural land, while low-risk clusters were characterised by urban land and open land other than agricultural land. CONCLUSIONS/INTERPRETATION: Our findings suggest that the development of type 1 diabetes in Sweden varies geographically and is associated with specific features of the local surroundings in early childhood. This is important knowledge as a basis for identifying possible environmental risk factors and the relationship with risk of type 1 diabetes in future studies.

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