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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Associations between data-driven lifestyle profiles and cognitive function in the AusDiab study
|
|---|---|
| Published in |
BMC Public Health, November 2022
|
| DOI | 10.1186/s12889-022-14379-z |
| Pubmed ID | |
| Authors |
Sara E Dingle, Steven J Bowe, Melissa Bujtor, Catherine M Milte, Robin M Daly, Kaarin J Anstey, Jonathan E Shaw, Susan J Torres |
| Abstract |
Mounting evidence highlights the importance of combined modifiable lifestyle factors in reducing risk of cognitive decline and dementia. Several a priori additive scoring approaches have been established; however, limited research has employed advanced data-driven approaches to explore this association. This study aimed to examine the association between data-driven lifestyle profiles and cognitive function in community-dwelling Australian adults. A cross-sectional study of 4561 Australian adults (55.3% female, mean age 60.9 ± 11.3 years) was conducted. Questionnaires were used to collect self-reported data on diet, physical activity, sedentary time, smoking status, and alcohol consumption. Cognitive testing was undertaken to assess memory, processing speed, and vocabulary and verbal knowledge. Latent Profile Analysis (LPA) was conducted to identify subgroups characterised by similar patterns of lifestyle behaviours. The resultant subgroups, or profiles, were then used to further explore associations with cognitive function using linear regression models and an automatic Bolck, Croon & Hagenaars (BCH) approach. Three profiles were identified: (1) "Inactive, poor diet" (76.3%); (2) "Moderate activity, non-smokers" (18.7%); and (3) "Highly active, unhealthy drinkers" (5.0%). Profile 2 "Moderate activity, non-smokers" exhibited better processing speed than Profile 1 "Inactive, poor diet". There was also some evidence to suggest Profile 3 "Highly active, unhealthy drinkers" exhibited poorer vocabulary and verbal knowledge compared to Profile 1 and poorer processing speed and memory scores compared to Profile 2. In this population of community-dwelling Australian adults, a sub-group characterised by moderate activity levels and higher rates of non-smoking had better cognitive function compared to two other identified sub-groups. This study demonstrates how LPA can be used to highlight sub-groups of a population that may be at increased risk of dementia and benefit most from lifestyle-based multidomain intervention strategies. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 4 | 67% |
| Curaçao | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Members of the public | 2 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 15% |
| Student > Ph. D. Student | 2 | 10% |
| Researcher | 2 | 10% |
| Student > Bachelor | 1 | 5% |
| Unknown | 12 | 60% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 3 | 15% |
| Medicine and Dentistry | 2 | 10% |
| Unspecified | 1 | 5% |
| Nursing and Health Professions | 1 | 5% |
| Chemical Engineering | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 12 | 60% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 01 December 2022.
All research outputs
#6,706,056
of 23,801,276 outputs
Outputs from BMC Public Health
#6,984
of 15,414 outputs
Outputs of similar age
#126,209
of 460,721 outputs
Outputs of similar age from BMC Public Health
#130
of 429 outputs
Altmetric has tracked 23,801,276 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 15,414 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one has gotten more attention than average, scoring higher than 54% of its peers.
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 460,721 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 429 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.