Geographical clustering and socioeconomic factors associated with hypoglycemic events requiring emergency assistance in Andalusia (Spain).

INTRODUCTION

The geographical distribution of hypoglycemic events requiring emergency assistance was explored in Andalusia (Spain), and potentially associated societal factors were determined.

RESEARCH DESIGN AND METHODS

This was a database analysis of hypoglycemia requiring prehospital emergency assistance from the Public Company for Health Emergencies ( (EPES)) in Andalusia during 2012, which served 8 393 159 people. Databases of the National Statistics Institute, Basic Spatial Data of Andalusia and System of Multiterritorial Information of Andalusia were used to retrieve spatial data and population characteristics. Geographic Information System software ( and ) was used for analysis and linkage across databases. Spatial analyses of geographical location influence in hypoglycemic events were assessed using Moran's I statistics, and linear regressions were used to determine their association with population characteristics.

RESULTS

The EPES attended 1 137 738 calls requesting medical assistance, with a mean hypoglycemia incidence of 95.0±61.6 cases per 100 000 inhabitants. There were significant differences in hypoglycemia incidence between basic healthcare zones attributable to their geographical location in the overall population (Moran's I index 0.122, z-score 7.870, p=0.001), women (Moran's I index 0.088, z-score 6.285, p=0.001), men (Moran's I index 0.076, z-score 4.914, p=0.001) and aged >64 years (Moran's I index 0.147, z-score 9.753, p=0.001). Hypoglycemia incidence was higher within unemployed individuals (β=0.003, p=0.001) and unemployed women (β=0.005, p=0.001), while lower within individuals aged <16 years (β=-0.004, p=0.040), higher academic level (secondary studies) (β=-0.003, p=0.004) and women with secondary studies (β=-0.005, p<0.001). In subjects aged >64 years, lower rate of hypoglycemia was associated with more single-person homes (β=-0.008, p=0.022) and sports facilities (β=-0.342, p=0.012).

CONCLUSIONS

This analysis supports the geographical distribution of hypoglycemia in the overall population, both genders and subjects aged >64 years, which was affected by societal factors such as unemployment, literacy/education, housing and sports facilities. These data can be useful to design specific prevention programs.