A comparison of complementary and alternative medicine users and use across geographical areas: A national survey of 1,427 women
1 Faculty of Nursing Midwifery and Health, University of Technology Sydney, Sydney, New South Wales, Australia
2 School of Medicine and Public Health, University of Newcastle, New South Wales, Australia
3 School of Population Health, University of Queensland, Brisbane, Queensland, Australia
4 School of Social Science, University of Queensland, Brisbane, Queensland, Australia
5 Priority Research Centre for Gender, Health and Ageing, University of Newcastle, New South Wales, Australia
6 School of Rural Health, Monash University, Bendigo, Victoria, Australia
7 Department of General Practice, University of Melbourne, Victoria, Australia
8 Network of Researchers in the Public Health of Complementary and Alternative Medicine (NORPHCAM), Faculty of Nursing, Midwifery and Health, University of Technology, Level 7 Building 10, 235-253 Jones St, Ultimo New South Wales, 2007, Australia
BMC Complementary and Alternative Medicine 2011, 11:85 doi:10.1186/1472-6882-11-85Published: 7 October 2011
Evidence indicates that people who reside in non-urban areas have a higher use of complementary and alternative medicine (CAM) than people who reside in urban areas. However, there is sparse research on the reasons for such differences. This paper investigates the reasons for geographical differences in CAM use by comparing CAM users from four geographical areas (major cities, inner regional, outer region, rural/remote) across a range of health status, healthcare satisfaction, neighbourhood and community factors.
A cross-sectional survey of 1,427 participants from the Australian Longitudinal Study on Women's Health (ALSWH) conducted in 2009.
The average total cost of consultations with CAM practitioners was $416 per annum and was highest for women in the major cities, declining with increasing distance from capital cities/remoteness (p < 0.001). The average total cost of self-prescribed CAM was $349 per annum, but this did not significantly differ across geographical areas. The increased use of CAM in rural and remote areas appears to be influenced by poorer access to conventional medical care (p < 0.05) and a greater sense of community (p < 0.05) amongst these rural and remote residents. In contrast to the findings of previous research this study found that health status was not associated with the differences in CAM use between urban and non-urban areas.
It appears that a number of factors influence the different levels of CAM use across the urban/non-urban divide. Further research is needed to help tease out and understand these factors. Such research will help support health care policy and practice with regards to this topic.