OBJECTIVE: To investigate and monitor the patterns in incidence of childhood type 1 diabetes worldwide. RESEARCH DESIGN AND METHODS: The incidence of type 1 diabetes (per 100,000 per year) from 1990 to 1994 was determined in children < or =14 years of age from 100 centers in 50 countries. A total of 19,164 cases were diagnosed in study populations totaling 75.1 million children. The annual incidence rates were calculated per 100,000 population. RESULTS: The overall age-adjusted incidence of type 1 diabetes varied from 0.1/100,000 per year in China and Venezuela to 36.8/100,000 per year in Sardinia and 36.5/100,000 per year in Finland. This represents a >350-fold variation in the incidence among the 100 populations worldwide. The global pattern of variation in incidence was evaluated by arbitrarily grouping the populations with a very low (<1/100,000 per year), a low (1-4.99/100,000 per year), an intermediate (5-9.99/100,000 per year), a high (10-19.99/100,000 per year), and a very high (> or =20/100,000 per year) incidence. Of the European populations, 18 of 39 had an intermediate incidence, and the remainder had a high or very high incidence. A very high incidence (> or =20/ 100,000 per year) was found in Sardinia, Finland, Sweden, Norway Portugal, the U.K., Canada, and New Zealand. The lowest incidence (<1/100,000 per year) was found in the populations from China and South America. In most populations, the incidence increased with age and was the highest among children 10-14 years of age. CONCLUSIONS: The range of global variation in the incidence of childhood type 1 diabetes is even larger than previously described. The earlier reported polar-equatorial gradient in the incidence does not seem to be as strong as previously assumed, but the variation seems to follow ethnic and racial distribution in the world population.

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Study objective: To examine the association of spatial variation in acute myocardial infarction (AMI) incidence and its putative environmental determinants in ground water such as total water hardness, the concentration of calcium, magnesium, fluoride, iron, copper, zinc, nitrate, and aluminium. Design: Small area study using Bayesian modelling and the geo-referenced data aggregated into 10 km610 km cells. Setting: The population data were obtained from Statistics Finland, AMI case data from the National Death Register and the Hospital Discharge Register, and the geochemical data from hydrogeochemical database of Geological Survey of Finland. Participants: A total of 18 946 men aged 35-74 years with the first AMI attack in the years 1983, 1988, and 1993. Main results: One unit (in German degree˚dH) increment in water hardness decreased the risk of AMI by 1%. Geochemical elements in ground water included in this study did not show a statistically significant effect on the incidence and spatial variation of AMI, even though suggestive findings were detected for fluoride (protective), iron and copper (increasing). Conclusions:The results of this study with more specific Bayesian statistical analysis confirm findings from earlier observations of the inverse relation between water hardness and coronary heart disease. The role of environmental geochemistry in the geographical variation of the AMI incidence should be studied further in more detail incorporating the individual intake of both food borne and water borne nutrients. Geochemical-spatial analysis provides a basis for the selection of areas suitable for such research.

In this paper, the spatial distribution of the first event of acute myocardial infarction among 35- to 74-year-old men in Finland was examined for the cross-section years 1983, 1988 and 1993. The analysis was performed using a Bayesian hierarchical spatial approach to the geographically referenced data. The population data and case data received from nationwide registries were aggregated into 10 × 10 km cells. The estimated maps show that along with the overall decreasing incidence, the high-risk area withdrew deeper into the northeast, with an incidence 7–12% higher in rural than in urban areas. It could be concluded that eastern Finland is likely to remain a high-risk area in the future due to the concentration of certain risk factors.

Detection of high-risk areas in both provinces showed that underlying environmental and/or genetic risk factors of AMI are not evenly distributed within the province but enriched in certain geographical non-administratively defined locations in eastern Finland.