Home truths and cool admissions: New Zealand housing attributes and excess winter hospitalisation

Lucy Telfar-Barnard – PhD 2010

Background: The ratio of winter to non-winter mortality rates, or excess winter mortality (EWM), is higher in temperate countries, including New Zealand. Many studies suggest housing differences as a possible explanation. Home heating and insulation levels have been found to be associated with health outcomes and some studies have implicated housing faults as contributing to EWM. In contrast, excess winter hospitalisation (EWH) in general, and the contribution housing makes to EWH in particular, has been little explored.

Aims: This research aimed to describe EWH, and investigate whether housing attributes were associated with any excess.

Method: A retrospective cohort study was conducted of 1,596,126 acute overnight hospitalisations, over 11,477,510,015 person days, between 1 February 2000 and 31 January 2006, using the full National Health Index (NHI) database as the cohort. Using address data, 2,405,070 NHI records were matched to 689,185 Quotable Value NZ Ltd (QV) dwelling records. Winter was defined as 1 June to 30 September. Poisson regressions with robust standard errors were used to calculate both winter:non-winter incidence rate ratios (also known as the excess winter hospitalisation index, or EWHI) and relative rate ratios (RRR). RRRs were used to identify differences in EWHI within demographic variables earlier found to be associated with level of winter excess (sex, age, ethnicity, and Census meshblock rurality, NZDep decile, and annual average minimum outdoor temperature) and within the dwelling attributes (construction decade, insulation era, dwelling type, floor area, condition, tenure index, and capital value).

Results: Hospitalisation rates were 8.3% higher in winter than the rest of the year, with 7,166 excess winter hospitalisations per year. All-cause EWHIs were highest in the very young and older people, higher for women than for men, and higher in Māori and Pacific Peoples than in NZ Europeans. However, the higher EWHI for Māori was due to higher rates of respiratory illness (which has the highest EWHI). EWHIs increased with increasing socio-economic deprivation (NZDep decile) and with decreasing annual average minimum temperature, but were lower in Rural Centres than in Main Urban areas. Similar patterns for age, gender, NZDep and temperature were observed in respiratory EWHIs, but while Pacific Peoples had higher respiratory EWHIs than NZ Europeans, Māori did not. Only age showed significant differences in circulatory EWHIs.

By dwelling type, EWHIs were higher in Villas (RRR 1.0297, 95% CI 1.0012-1.0591, p=0.041) and in Pre-war Bungalows (RRR 1.0296, 95% CI 1.0089-1.0506, p=0.005) than in Post-war Bungalows, and lower in Quality Bungalows (RRR 0.9781, 95% CI 0.9580-0.9985, p=0.036). EWHIs also increased as the proportion of rental households in a Census meshblock increased, and NZ Europeans living in “Poor” condition dwellings had higher EWHIs than those living in “Superior” dwellings. There was no difference in EWHIs by construction decade or insulation era.

Conclusion: Both demographic and environmental factors are associated with differences in EWHIs. Dwelling type is associated with EWH and probably overall hospitalisation rates. Further research to identify whether dwelling design or construction features are behind these differences in EWHIs could suggest areas for public health intervention.

Read Lucy’s Thesis