Modeling the geographic distribution of serious mental illness in New Zealand

This study aims to estimate, apply, and validate a model of the risk of serious mental illness (SMI) in local service areas
throughout New Zealand.

The study employs a secondary analysis of data from the Te Rau Hinengaro Mental Health Survey of 12,992 adults aged 16 years
and over from the household population. It uses small area estimation (SAE) methods involving: (1) estimation of a logistic
model of risk of SMI; (2) use of the foregoing model for computing estimates, using census data, for District Board areas;
(3) validation of estimates against an alternative indicator of SMI prevalence.

The model uses age, ethnicity, marital status, employment, and income to predict 92.2 % of respondents’ SMI statuses, with
a specificity of 95.9 %, sensitivity of 16.9 %, and an AUC of 0.73. The resulting estimates for the District Board areas ranged
between 4.1 and 5.7 %, with confidence intervals from ±0.3 to ±1.1 %. The estimates demonstrated a correlation of 0.51 (p = 0.028) with rates of psychiatric hospitalization.

The use of SAE methods demonstrated the capacity for deriving local prevalence rates of SMI, which can be validated against
an available indicator.