Can a deterministic spatial microsimulation model provide reliable small-area estimates of health behaviours? An example of smoking prevalence in New Zealand.
Models created to estimate neighbourhood level health outcomes and behaviours can be difficult to validate as prevalence is often unknown at the local level. This paper tests the reliability of a spatial microsimulation model, using a deterministic reweighting method, to predict smoking prevalence in small areas across New Zealand. The difference in the prevalence of smoking between those estimated by the model and those calculated from census data is less than 20% in 1745 out of 1760 areas. The accuracy of these results provides users with greater confidence to utilize similar approaches in countries where local-level smoking prevalence is unknown.
Department of Geography, Queen Mary, University of London, 327 Mile End Road, London E1 4NS, UK. d.smith@qmul.ac.uk
Dianna M
DM
Smith
Jamie R
JR
Pearce
Kirk
K
Harland
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D015438:Health Behavior; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009520:New Zealand / Q000453:epidemiology; D015203:Reproducibility of Results; D012111:Residence Characteristics; D017062:Small-Area Analysis; D012907:Smoking / Q000453:epidemiology*