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      Unmasking hidden disparities: a comparative observational study examining the impact of different rurality classifications for health research in Aotearoa New Zealand

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          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.

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          Most cited references25

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            Stata Stastistical Software: Release 17

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              Addressing the health disadvantage of rural populations: how does epidemiological evidence inform rural health policies and research?

              We reviewed evidence of any apparently significant 'rural-urban' health status differentials in developed countries, to determine whether such differentials are generic or nation-specific, and to explore the nature and policy implications of determinants underpinning rural-urban health variations. A comprehensive literature review of rural-urban health status differentials within Australia, New Zealand, Canada, the USA, the UK, and a variety of other western European nations was undertaken to understand the differences in life expectancy and cause-specific morbidity and mortality. While rural location plays a major role in determining the nature and level of access to and provision of health services, it does not always translate into health disadvantage. When controlling for major risk determinants, rurality per se does not necessarily lead to rural-urban disparities, but may exacerbate the effects of socio-economic disadvantage, ethnicity, poorer service availability, higher levels of personal risk and more hazardous environmental, occupational and transportation conditions. Programs to improve rural health will be most effective when based on policies which target all risk determinants collectively contributing to poor rural health outcomes. Focusing solely on 'area-based' explanations and responses to rural health problems may divert attention from more fundamental social and structural processes operating in the broader context to the detriment of rural health policy formulation and remedial effort.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2023
                13 April 2023
                : 13
                : 4
                : e067927
                Affiliations
                [1 ]departmentDepartment of General Practice and Rural Health , Ringgold_2495University of Otago , Dunedin, New Zealand
                [2 ]departmentTe Ngira: Institute for Population Research , Ringgold_3717The University of Waikato , Hamilton, New Zealand
                [3 ]departmentDepartment of Preventive and Social Medicine , University of Otago , Dunedin, New Zealand
                [4 ]departmentWaikato Medical Research Centre , Ringgold_3717The University of Waikato , Hamilton, New Zealand
                [5 ]Te Whatu Ora - Waikato , Hamilton, New Zealand
                [6 ]Te Whatu Ora - Waikato , Thames, New Zealand
                Author notes
                [Correspondence to ] Dr Jesse Whitehead; Jesse.whitehead@ 123456waikato.ac.nz
                Author information
                http://orcid.org/0000-0001-9682-7544
                http://orcid.org/0000-0001-5466-5364
                http://orcid.org/0000-0001-9367-1492
                http://orcid.org/0000-0002-4221-6892
                Article
                bmjopen-2022-067927
                10.1136/bmjopen-2022-067927
                10106021
                37055208
                3f305a0b-5b1c-4fc1-ae6a-a86dfb471aa1
                © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 03 September 2022
                : 28 March 2023
                Funding
                Funded by: The Health Research Council of New Zealand;
                Award ID: HRC19/488
                Categories
                Epidemiology
                1506
                1692
                Original research
                Custom metadata
                unlocked

                Medicine
                epidemiology,health policy,public health,statistics & research methods
                Medicine
                epidemiology, health policy, public health, statistics & research methods

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