Geographic weighted regression: applicability to epidemiological studies of leprosy
Rev. Soc. Bras. Med. Trop
;
49(1): 74-82, Jan.-Feb. 2016. tab, graf
Article
Dans Anglais
| LILACS
| ID: lil-776536
ABSTRACT
Abstract INTRODUCTION:
Geographic information systems (GIS) enable public health data to be analyzed in terms of geographical variability and the relationship between risk factors and diseases. This study discusses the application of the geographic weighted regression (GWR) model to health data to improve the understanding of spatially varying social and clinical factors that potentially impact leprosy prevalence.METHODS:
This ecological study used data from leprosy case records from 1998-2006, aggregated by neighborhood in the Duque de Caxias municipality in the State of Rio de Janeiro, Brazil. In the GWR model, the associations between the log of the leprosy detection rate and social and clinical factors were analyzed.RESULTS:
Maps of the estimated coefficients by neighborhood confirmed the heterogeneous spatial relationships between the leprosy detection rates and the predictors. The proportion of households with piped water was associated with higher detection rates, mainly in the northeast of the municipality. Indeterminate forms were strongly associated with higher detections rates in the south, where access to health services was more established.CONCLUSIONS:
GWR proved a useful tool for epidemiological analysis of leprosy in a local area, such as Duque de Caxias. Epidemiological analysis using the maps of the GWR model offered the advantage of visualizing the problem in sub-regions and identifying any spatial dependence in the local study area.
Texte intégral:
Disponible
Indice:
LILAS (Amériques)
Sujet Principal:
Géographie médicale
/
Lèpre
Type d'étude:
Etude d'étiologie
/
Étude observationnelle
/
Étude de prévalence
/
Étude pronostique
/
Facteurs de risque
Limites du sujet:
Humains
Pays comme sujet:
Amérique du Sud
/
Brésil
langue:
Anglais
Texte intégral:
Rev. Soc. Bras. Med. Trop
Thème du journal:
Médecine tropicale
Année:
2016
Type:
Article
Pays d'affiliation:
Brésil
Institution/Pays d'affiliation:
Secretaria Municipal de Saúde de Duque de Caxias/BR
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