Skip header and navigation

1 records – page 1 of 1.

Accessibility to health care facilities in Montreal Island: an application of relative accessibility indicators from the perspective of senior and non-senior residents.

https://arctichealth.org/en/permalink/ahliterature139831
Source
Int J Health Geogr. 2010;9:52
Publication Type
Article
Date
2010
Author
Antonio Paez
Ruben G Mercado
Steven Farber
Catherine Morency
Matthew Roorda
Author Affiliation
School of Geography and Earth Sciences, McMaster University, Hamilton Ontario, Canada. paezha@mcmaster.ca
Source
Int J Health Geogr. 2010;9:52
Date
2010
Language
English
Publication Type
Article
Keywords
Adult
Age Factors
Aged
Health Services Accessibility - statistics & numerical data
Humans
Middle Aged
Mobility Limitation
Quebec
Regression Analysis
Residence Characteristics
Socioeconomic Factors
Transportation - statistics & numerical data
Young Adult
Abstract
Geographical access to health care facilities is known to influence health services usage. As societies age, accessibility to health care becomes an increasingly acute public health concern. It is known that seniors tend to have lower mobility levels, and it is possible that this may negatively affect their ability to reach facilities and services. Therefore, it becomes important to examine the mobility situation of seniors vis-a-vis the spatial distribution of health care facilities, to identify areas where accessibility is low and interventions may be required.
Accessibility is implemented using a cumulative opportunities measure. Instead of assuming a fixed bandwidth (i.e. a distance threshold) for measuring accessibility, in this paper the bandwidth is defined using model-based estimates of average trip length. Average trip length is an all-purpose indicator of individual mobility and geographical reach. Adoption of a spatial modelling approach allows us to tailor these estimates of travel behaviour to specific locations and person profiles. Replacing a fixed bandwidth with these estimates permits us to calculate customized location- and person-based accessibility measures that allow inter-personal as well as geographical comparisons.
The case study is Montreal Island. Geo-coded travel behaviour data, specifically average trip length, and relevant traveller's attributes are obtained from the Montreal Household Travel Survey. These data are complemented with information from the Census. Health care facilities, also geo-coded, are extracted from a comprehensive business point database. Health care facilities are selected based on Standard Industrial Classification codes 8011-21 (Medical Doctors and Dentists).
Model-based estimates of average trip length show that travel behaviour varies widely across space. With the exception of seniors in the downtown area, older residents of Montreal Island tend to be significantly less mobile than people of other age cohorts. The combination of average trip length estimates with the spatial distribution of health care facilities indicates that despite being more mobile, suburban residents tend to have lower levels of accessibility compared to central city residents. The effect is more marked for seniors. Furthermore, the results indicate that accessibility calculated using a fixed bandwidth would produce patterns of exposure to health care facilities that would be difficult to achieve for suburban seniors given actual mobility patterns.
The analysis shows large disparities in accessibility between seniors and non-seniors, between urban and suburban seniors, and between vehicle owning and non-owning seniors. This research was concerned with potential accessibility levels. Follow up research could consider the results reported here to select case studies of actual access and usage of health care facilities, and related health outcomes.
Notes
Cites: Soc Work. 1995 May;40(3):365-737761923
Cites: JAMA. 2002 Mar 13;287(10):1288-9411886320
Cites: J Dent Educ. 2005 Sep;69(9):961-7416141082
Cites: Health Policy. 2007 Mar;80(3):483-9116781002
Cites: Health Soc Work. 2007 Feb;32(1):57-6517432742
Cites: Int J Health Geogr. 2008;7:718282284
Cites: Ann N Y Acad Sci. 2008;1136:149-6017954671
Cites: Ann N Y Acad Sci. 2008;1136:161-7117954679
Cites: Int J Health Geogr. 2008;7:6319087277
Cites: Health Place. 2009 Dec;15(4):1100-719576837
Cites: Int J Health Geogr. 2010;9:1720298608
Cites: MMWR CDC Surveill Summ. 1999 Dec 17;48(8):51-8810634271
Cites: Ann N Y Acad Sci. 1999;896:497-50010681961
Cites: J Womens Health Gend Based Med. 2000 Oct;9(8):881-911074954
Cites: J Gerontol B Psychol Sci Soc Sci. 2001 Mar;56(2):S69-8311245367
Cites: Health Soc Care Community. 2001 Jan;9(1):11-811560717
Cites: J Health Care Poor Underserved. 2002 Feb;13(1):95-11111836917
Cites: Issue Brief Cent Stud Health Syst Change. 2002 Feb;(49):1-411865909
Cites: Med Care Res Rev. 2002 Mar;59(1):79-98; discussion 99-10311877880
Cites: Am J Public Health. 1993 Jul;83(7):948-548328615
Cites: J Rural Health. 1991;7(4 Suppl):437-5010116034
Cites: Int J Health Serv. 1978;8(3):519-30681049
Cites: Am J Public Health. 2004 Oct;94(10):1788-9415451751
Cites: Health Place. 2004 Sep;10(3):273-8315177201
Cites: Health Serv Res. 2003 Feb;38(1 Pt 1):287-30912650392
Cites: Int J Health Serv. 2002;32(1):89-10611913859
Cites: Ambul Pediatr. 2001 Jan-Feb;1(1):3-1511888366
Cites: Health Place. 2005 Jun;11(2):131-4615629681
PubMed ID
20973969 View in PubMed
Less detail