Jesse Whitehead, Gabrielle Davie, Brandon de Graaf, Sue Crengle, Ross Lawrenson, Rory Miller, and Garry Nixon. “Unmasking hidden disparities: a comparative observational study examining the impact of different rurality classifications for health research in Aotearoa New Zealand.” BMJ open 13, no. 4 (2023): e067927.

OPEN ACCESS: https://bmjopen.bmj.com/content/13/4/e067927.info

The key outcome of this paper is how rural health outcomes have been underestimated by previous rurality classifications for many years. Using the Geographic Classification for Health (GCH) in any future rural-urban health analysis is encouraged.

 

 

Abstract

Objectives 

Examine the impact of two generic—urban–rural experimental profile (UREP) and urban accessibility (UA)—and one purposely built—geographic classification for health (GCH)—rurality classification systems on the identification of rural–urban health disparities in Aotearoa New Zealand (NZ).

Design 

A comparative observational study.

Setting 

NZ; the most recent 5 years of available data on mortality events (2013–2017), hospitalisations and non-admitted hospital patient events (both 2015–2019).

Participants 

Numerator data included deaths (n=156 521), hospitalisations (n=13 020 042) and selected non-admitted patient events (n=44 596 471) for the total NZ population during the study period. Annual denominators, by 5-year age group, sex, ethnicity (Māori, non-Māori) and rurality, were estimated from Census 2013 and Census 2018.

Primary and secondary outcome measures 

Primary measures were the unadjusted rural incidence rates for 17 health outcome and service utilisation indicators, using each rurality classification. Secondary measures were the age-sex-adjusted rural and urban incidence rate ratios (IRRs) for the same indicators and rurality classifications.

Results 

Total population rural rates of all indicators examined were substantially higher using the GCH compared with the UREP, and for all except paediatric hospitalisations when the UA was applied. All-cause rural mortality rates using the GCH, UA and UREP were 82, 67 and 50 per 10 000 person-years, respectively. Rural–urban all-cause mortality IRRs were higher using the GCH (1.21, 95% CI 1.19 to 1.22), compared with the UA (0.92, 95% CI 0.91 to 0.94) and UREP (0.67, 95% CI 0.66 to 0.68). Age-sex-adjusted rural and urban IRRs were also higher using the GCH than the UREP for all outcomes, and higher than the UA for 13 of the 17 outcomes. A similar pattern was observed for Māori with higher rural rates for all outcomes using the GCH compared with the UREP, and 11 of the 17 outcomes using the UA. For Māori, rural–urban all-cause mortality IRRs for Māori were higher using the GCH (1.34, 95% CI 1.29 to 1.38), compared with the UA (1.23, 95% CI 1.19 to 1.27) and UREP (1.15, 95% CI 1.10 to 1.19).

Conclusions 

Substantial variation in rural health outcome and service utilisation rates were identified with different classifications. Rural rates using the GCH are substantially higher than the UREP. Generic classifications substantially underestimated rural–urban mortality IRRs for the total and Māori populations.