↓ Skip to main content

Life course trajectories of alcohol consumption in the United Kingdom using longitudinal data from nine cohort studies

Overview of attention for article published in BMC Medicine, March 2015
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)

Mentioned by

news
32 news outlets
blogs
2 blogs
twitter
67 tweeters
facebook
7 Facebook pages
reddit
2 Redditors
video
1 video uploader

Citations

dimensions_citation
110 Dimensions

Readers on

mendeley
145 Mendeley
citeulike
1 CiteULike
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
Life course trajectories of alcohol consumption in the United Kingdom using longitudinal data from nine cohort studies
Published in
BMC Medicine, March 2015
DOI 10.1186/s12916-015-0273-z
Pubmed ID
Authors

Annie Britton, Yoav Ben-Shlomo, Michaela Benzeval, Diana Kuh, Steven Bell

Abstract

Alcohol consumption patterns change across life and this is not fully captured in cross-sectional series data. Analysis of longitudinal data, with repeat alcohol measures, is necessary to reveal changes within the same individuals as they age. Such data are scarce and few studies are able to capture multiple decades of the life course. Therefore, we examined alcohol consumption trajectories, reporting both average weekly volume and frequency, using data from cohorts with repeated measures that cover different and overlapping periods of life. Data were from nine UK-based prospective cohorts with at least three repeated alcohol consumption measures on individuals (combined sample size of 59,397 with 174,666 alcohol observations), with data spanning from adolescence to very old age (90 years plus). Information on volume and frequency of drinking were harmonised across the cohorts. Predicted volume of alcohol by age was estimated using random effect multilevel models fitted to each cohort. Quadratic and cubic polynomial terms were used to describe non-linear age trajectories. Changes in drinking frequency by age were calculated from observed data within each cohort and then smoothed using locally weighted scatterplot smoothing. Models were fitted for men and women separately. We found that, for men, mean consumption rose sharply during adolescence, peaked at around 25 years at 20 units per week, and then declined and plateaued during mid-life, before declining from around 60 years. A similar trajectory was seen for women, but with lower overall consumption (peak of around 7 to 8 units per week). Frequent drinking (daily or most days of the week) became more common during mid to older age, most notably among men, reaching above 50% of men. This is the first attempt to synthesise longitudinal data on alcohol consumption from several overlapping cohorts to represent the entire life course and illustrates the importance of recognising that this behaviour is dynamic. The aetiological findings from epidemiological studies using just one exposure measure of alcohol, as is typically done, should be treated with caution. Having a better understanding of how drinking changes with age may help design intervention strategies.

Twitter Demographics

The data shown below were collected from the profiles of 67 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 144 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 18%
Student > Bachelor 23 16%
Researcher 23 16%
Student > Ph. D. Student 20 14%
Student > Doctoral Student 10 7%
Other 29 20%
Unknown 14 10%
Readers by discipline Count As %
Medicine and Dentistry 39 27%
Psychology 22 15%
Pharmacology, Toxicology and Pharmaceutical Science 13 9%
Social Sciences 12 8%
Nursing and Health Professions 7 5%
Other 23 16%
Unknown 29 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 309. 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 19 January 2019.
All research outputs
#53,074
of 16,116,390 outputs
Outputs from BMC Medicine
#54
of 2,517 outputs
Outputs of similar age
#850
of 219,113 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 16,116,390 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,517 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.5. This one has done particularly well, scoring higher than 97% 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 219,113 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them