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Role of Area-Level Access to Primary Care on the Geographic Variation of Cardiometabolic Risk Factor Distribution: A Multilevel Analysis of the Adult Residents in the Illawarra—Shoalhaven Region of NSW, Australia

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  • Renin Toms

    (School of Medicine, University of Wollongong, Wollongong NSW 2522, Australia
    Illawarra Health and Medical Research Institute, Wollongong NSW 2522, Australia)

  • Xiaoqi Feng

    (Illawarra Health and Medical Research Institute, Wollongong NSW 2522, Australia
    Population Wellbeing and Environment Research Lab (PowerLab), School of Health and Society, Faculty of Social Sciences, University of Wollongong, Wollongong NSW 2500, Australia
    School of Public Health and Community Medicine, University of New South Wales, Sydney NSW 2033, Australia)

  • Darren J Mayne

    (School of Medicine, University of Wollongong, Wollongong NSW 2522, Australia
    Illawarra Health and Medical Research Institute, Wollongong NSW 2522, Australia
    Illawarra Shoalhaven Local Health District, Public Health Unit, Warrawong NSW 2502, Australia
    School of Public Health, The University of Sydney, Sydney NSW 2006, Australia)

  • Andrew Bonney

    (School of Medicine, University of Wollongong, Wollongong NSW 2522, Australia
    Illawarra Health and Medical Research Institute, Wollongong NSW 2522, Australia)

Abstract

Background: Access to primary care is important for the identification, control and management of cardiometabolic risk factors (CMRFs). This study investigated whether differences in geographic access to primary care explained area-level variation in CMRFs. Methods: Multilevel logistic regression models were used to derive the association between area-level access to primary care and seven discrete CMRFs after adjusting for individual and area-level co-variates. Two-step floating catchment area method was used to calculate the geographic access to primary care for the small areas within the study region. Results: Geographic access to primary care was inversely associated with low high density lipoprotein (OR 0.94, CI 0.91–0.96) and obesity (OR 0.91, CI 0.88–0.93), after adjusting for age, sex and area-level disadvantage. The intra-cluster correlation coefficient (ICCs) of all the fully adjusted models ranged between 0.4–1.8%, indicating low general contextual effects of the areas on CMRF distribution. The area-level variation in CMRFs explained by primary care access was ≤10.5%. Conclusion: The findings of the study support proportionate universal interventions for the prevention and control of CMRFs, rather than any area specific interventions based on their primary care access, as the contextual influence of areas on all the analysed CMRFs were found to be minimal. The findings also call for future research that includes other aspects of primary care access, such as road-network access, financial affordability and individual-level acceptance of the services in order to gain an overall picture of the area-level contributing role of primary care on CMRFs in the study region.

Suggested Citation

  • Renin Toms & Xiaoqi Feng & Darren J Mayne & Andrew Bonney, 2020. "Role of Area-Level Access to Primary Care on the Geographic Variation of Cardiometabolic Risk Factor Distribution: A Multilevel Analysis of the Adult Residents in the Illawarra—Shoalhaven Region of NS," IJERPH, MDPI, vol. 17(12), pages 1-21, June.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:12:p:4297-:d:372174
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    References listed on IDEAS

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