Is Walk Score associated with hospital admissions from chronic diseases? Evidence from a cross-sectional study in a high socioeconomic status Australian city-state

Soumya Mazumdar; Vincent Learnihan; Thomas Cochrane; Hai Phung; Bridget O'Connor; Rachel Davey

doi:10.1136/bmjopen-2016-012548

Is Walk Score associated with hospital admissions from chronic diseases? Evidence from a cross-sectional study in a high socioeconomic status Australian city-state

BMJ Open. 2016 Dec 8;6(12):e012548. doi: 10.1136/bmjopen-2016-012548.

Authors

Soumya Mazumdar^{1

2}, Vincent Learnihan², Thomas Cochrane², Hai Phung^{3

4}, Bridget O'Connor³, Rachel Davey²

Affiliations

¹ Epidemiology Group, Healthy People and Places Unit, South West Sydney Local Health District, New South Wales Health, Australia.
² The Centre for Research and Action in Public Health (CeRAPH), Health Research Institute, University of Canberra, Canberra, Australian Capital Territory, Australia.
³ Epidemiology Section, Health Improvement Branch Australian Capital Territory Health Directorate, Canberra, Australian Capital Territory, Australia.
⁴ School of Medicine, Griffith University, Gold Coast, Queensland, Australia.

Abstract

Objectives: To explore patterns of non-communicable diseases (NCDs) in the Australian Capital Territory (ACT).To ascertain the effect of the neighbourhood built environmental features and especially walkability on health outcomes, specifically for hospital admissions from NCDs.

Design: A cross-sectional analysis of public hospital episode data (2007-2013).

Setting: Hospitalisations from the ACT, Australia at very small geographic areas.

Participants: Secondary data on 75 290 unique hospital episodes representing 39 851 patients who were admitted to ACT hospitals from 2007 to 2013. No restrictions on age, sex or ethnicity.

Main exposure measures: Geographic Information System derived or compatible measures of general practitioner access, neighbourhood socioeconomic status, alcohol access, exposure to traffic and Walk Score walkability.

Main outcome measures: Hospitalisations of circulatory diseases, specific endocrine, nutritional and metabolic diseases, respiratory diseases and specific cancers.

Results: Geographic clusters with significant high and low risks of NCDs were found that displayed an overall geographic pattern of high risk in the outlying suburbs of the territory. Significant relationships between neighbourhood walkability as measured by Walk Score and the likelihood of hospitalisation with a primary diagnosis of myocardial infarction (heart attack) were found. A possible relationship was also found with the likelihood of being hospitalised with 4 major lifestyle-related cancers.

Conclusions: Our research augments the growing literature underscoring the relationships between the built environment and health outcomes. In addition, it supports the importance of walkable neighbourhoods, as measured by Walk Score, for improved health.

Keywords: Australia; Built Environment and Health; Chronic Diseases; Geographical Information Systems; Spatial Analysis; Walkability.

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MeSH terms

Australia
Chronic Disease* / therapy
Cities
Cross-Sectional Studies
Environment Design*
Female
Geographic Information Systems
Health Behavior
Hospitalization*
Humans
Life Style
Male
Myocardial Infarction* / prevention & control
Myocardial Infarction* / therapy
Neoplasms* / prevention & control
Neoplasms* / therapy
Noncommunicable Diseases / prevention & control
Noncommunicable Diseases / therapy
Residence Characteristics*
Social Class
Spatial Analysis
Suburban Population
Walking*