↓ Skip to main content

Variations in area-level disadvantage of Australian registered fitness trainers usual training locations

Overview of attention for article published in BMC Public Health, July 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
3 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
47 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Variations in area-level disadvantage of Australian registered fitness trainers usual training locations
Published in
BMC Public Health, July 2016
DOI 10.1186/s12889-016-3250-3
Pubmed ID
Authors

Jason A. Bennie, Lukar E. Thornton, Jannique G. Z. van Uffelen, Lauren K. Banting, Stuart J. H. Biddle

Abstract

Leisure-time physical activity and strength training participation levels are low and socioeconomically distributed. Fitness trainers (e.g. gym/group instructors) may have a role in increasing these participation levels. However, it is not known whether the training location and characteristics of Australian fitness trainers vary between areas that differ in socioeconomic status. In 2014, a sample of 1,189 Australian trainers completed an online survey with questions about personal and fitness industry-related characteristics (e.g. qualifications, setting, and experience) and postcode of their usual training location. The Australian Bureau of Statistics 'Index of Relative Socioeconomic Disadvantage' (IRSD) was matched to training location and used to assess where fitness professionals trained and whether their experience, qualification level and delivery methods differed by area-level disadvantage. Linear regression analysis was used to examine the relationship between IRSD score and selected characteristics adjusting for covariates (e.g. sex, age). Overall, 47 % of respondents worked in areas within the three least-disadvantaged deciles. In contrast, only 14.8 % worked in the three most-disadvantaged deciles. In adjusted regression models, fitness industry qualification was positively associated with a higher IRSD score (i.e. working in the least-disadvantaged areas) (Cert III: ref; Cert IV β:13.44 [95 % CI 3.86-23.02]; Diploma β:15.77 [95 % CI: 2.17-29.37]; Undergraduate β:23.14 [95 % CI: 9.41-36.86]). Fewer Australian fitness trainers work in areas with high levels of socioeconomic disadvantaged areas than in areas with low levels of disadvantage. A higher level of fitness industry qualifications was associated with working in areas with lower levels of disadvantage. Future research should explore the effectiveness of providing incentives that encourage more fitness trainers and those with higher qualifications to work in more socioeconomically disadvantaged areas.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 21%
Student > Bachelor 5 11%
Researcher 4 9%
Student > Ph. D. Student 4 9%
Other 2 4%
Other 6 13%
Unknown 16 34%
Readers by discipline Count As %
Sports and Recreations 12 26%
Social Sciences 5 11%
Nursing and Health Professions 5 11%
Environmental Science 2 4%
Business, Management and Accounting 2 4%
Other 7 15%
Unknown 14 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 July 2018.
All research outputs
#14,268,160
of 22,880,230 outputs
Outputs from BMC Public Health
#10,376
of 14,922 outputs
Outputs of similar age
#204,774
of 354,317 outputs
Outputs of similar age from BMC Public Health
#252
of 343 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,922 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 354,317 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 343 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.