Clustering of cases of type 1 diabetes in high socioeconomic communes in Santiago de Chile: spatio-temporal and geographical analysis

Abstract

The objective of this study was to describe spatial and space-time patterns of type 1 diabetes in children less than 15 years old, diagnosed between 2000 and 2005 with residence in the Metropolitan Region of Chile. Knox and Mantel tests were used to detect space-time interaction between cases. An ecological Bayesian model adjusted by socioeconomic factor and year was proposed to estimate the incidence by communes. Initially, there was no space-time interaction between cases, but there is evidence of clustering effect in urban areas of the region. The incidence rate for the overall study period was estimated by 6.18/100,000 (95% CI: 5.69-6.70), with a significant annual trend of 8.2% (P < 0.01). The geographical incidence could be explained by the human development index, as a socioeconomic factor. These results suggest that children living in communes with higher socioeconomic levels may be at higher risk of developing type 1 diabetes. Our findings support the hypothesis of an aetiological role of environmental factors in the onset of type 1 diabetes.

Spatial and temporal variation in type 1 diabetes incidence in Western Australia from 1991 to 2010: Increased risk at higher latitudes and over time

“…Whereas some studies show higher rates of T1DM in sparsely-populated rural areas than in urban areas (Cardwell et al, 2006;Holmqvist et al, 2008;Patterson and Waugh, 1992), other studies show the reverse pattern (Cherubini et al, 1999;Haynes et al, 2006) or no difference (Schober et al, 2003;Schoenle et al, 2001). Results for socioeconomic status are similarly diverse: high risk of T1DM has been variously associated with high socioeconomic status (Haynes et al, 2006;Patterson and Waugh, 1992;Siemiatycki et al, 1988;Tarn et al, 1983;Torres-Aviles et al, 2010), low socioeconomic status (Blom et al, 1989;Christau et al, 1977;Crow et al, 1991;Hungarian Childhood Diabetes Epidemiology Study Group, 1994;Waugh, 1986), or not at all (Bruno et al, 2000;Evans et al, 2000;Harron et al, 2011;Laporte et al, 1981).…”

Autism, Autoimmune Disease and Socioeconomic Status

“…Curiously, some autoimmune and inflammatory disorders, in particular type 1 diabetes, autoimmune thyroiditis, and asthma have been positively associated with high SES, and the study of SES and geographical clustering parallels that found in autism. Associations of type 1 diabetes and high SES have been found in diverse populations from the Unites States [52,53], Scotland [54], Sweden [55], Norway [56], Chile [57], and Australia [58]. Associations of high SES with asthma in Israel [59] and thyroid autoimmunity [60] in Russia versus Finland have also been reported.…”

¿El contexto geográfico importa en la mortalidad por diabetes mellitus? Tendencias espacio-temporales en Argentina, 1990-2012

“…La mayoría de los estudios dedicados a analizar la distribución espacial de la diabetes se han enfocado en la incidencia y prevalencia de la diabetes mellitus 1 12,13,14,15,16,17 , mientras que pocos estudios han analizado los patrones de distribución espacial de la enfermedad de la diabetes mellitus 2 18,19,20,21 . Green et al 19 demostraron que tasas altas de diabetes mellitus 2 se agrupaban significativamente en el espacio, de acuerdo con características étnicas, socioeconómicas, ambientales y de estilo de vida de la población de un área urbana de Canadá.…”