Int J Health Geogr - The effects of local street network characteristics on the positional accuracy of automated geocoding for geographic health studies.


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CKGROUND: Automated geocoding of patient addresses for the purpose of conducting spatial epidemiologic studies results in positional errors. It is well documented that errors tend to be larger in rural areas than in cities, but possible effects of local characteristics of the street network, such as street intersection density and street length, on errors have not yet been documented. Our study quantifies effects of these local street network characteristics on the means and the entire probability distributions of positional errors, using regression methods and tolerance intervals/regions, for more than 6000 geocoded patient addresses from an Iowa county.RESULTS: Positional errors were determined for 6376 addresses in Carroll County, Iowa, as the vector difference between each 100%-matched automated geocode and its ground-truthed location. Mean positional error magnitude was inversely related to proximate street intersection density. This effect was statistically significant for both rural and municipal addresses, but more so for the former. Also, the effect of street segment length on geocoding accuracy was statistically significant for municipal, but not rural, addresses; for municipal addresses mean error magnitude increased with length.CONCLUSION: Local street network characteristics may have statistically significant effects on geocoding accuracy in some places, but not others. Even in those locales where their effects are statistically significant, street network characteristics may explain a relatively small portion of the variability among geocoding errors. It appears that additional factors besides rurality and local street network characteristics affect accuracy in general.

Resumo Limpo

ckground autom geocod patient address purpos conduct spatial epidemiolog studi result posit error well document error tend larger rural area citi possibl effect local characterist street network street intersect densiti street length error yet document studi quantifi effect local street network characterist mean entir probabl distribut posit error use regress method toler intervalsregion geocod patient address iowa countyresult posit error determin address carrol counti iowa vector differ match autom geocod groundtruth locat mean posit error magnitud invers relat proxim street intersect densiti effect statist signific rural municip address former also effect street segment length geocod accuraci statist signific municip rural address municip address mean error magnitud increas lengthconclus local street network characterist may statist signific effect geocod accuraci place other even local effect statist signific street network characterist may explain relat small portion variabl among geocod error appear addit factor besid rural local street network characterist affect accuraci general

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