Estimating the incidence of dementia in New Zealand: a cohort study applying capture-recapture modelling to routinely collected linked health datasets

Abstract

Background

Issues of under-diagnosis and under-coding of dementia in routinely collected health data limit their utility for estimating dementia prevalence and incidence in Aotearoa New Zealand (NZ). Capture-recapture techniques can be used to estimate the number of dementia cases missing from health datasets by modelling the relationships and interactions between linked data sources. The aim of this study was to apply this technique to routinely collected and linked health datasets and more accurately estimate the incidence of dementia in NZ.

Methods

All incident cases of dementia in the NZ 60+ population were identified in three linked national health data sets—interRAI, Public hospital discharges, and Pharmacy. Capture-recapture analysis fitted eight loglinear models to the data, with the best fitting model used to estimate the number of cases missing from all three datasets, and thereby estimate the ‘true’ incidence of dementia. Incidence rates were calculated by 5-year age bands, sex and ethnicity.

Findings

Modelled estimates indicate 36% of incident cases are not present in any of the datasets. Modelled incidence rates in the 60+ age group were 19.2 (95% CI 17.3–22.0)/1000py, with an incident rate ratio of 1.9 (95% CI 1.9–2.0) per 5-year age band. There was no difference in incidence rates between males and females. Incidence rates in Asian (p < 0.001) but not Māori (p = 0.974) or Pacific peoples (p = 0.110) were significantly lower compared to Europeans, even after inclusion of missing cases.

Interpretation

This is the first study to provide estimates of age 60+ dementia incidence in NZ and for the four main ethnic groups and suggests over a third of incident dementia cases are undiagnosed. This highlights the need for better access to dementia assessment and diagnosis so that appropriate supports and interventions can be put in place to improve outcomes for people living with dementia and their families.

Funding

Nil.