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The socioeconomic profile of alcohol-attributable mortality in South Africa: a modelling study

Overview of attention for article published in BMC Medicine, June 2018
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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 (97th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
13 news outlets
policy
2 policy sources
twitter
20 tweeters

Citations

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25 Dimensions

Readers on

mendeley
146 Mendeley
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Title
The socioeconomic profile of alcohol-attributable mortality in South Africa: a modelling study
Published in
BMC Medicine, June 2018
DOI 10.1186/s12916-018-1080-0
Pubmed ID
Authors

Charlotte Probst, Charles D. H. Parry, Hans-Ulrich Wittchen, Jürgen Rehm

Abstract

Globally, illness and life expectancy follow a social gradient that puts people of lower socioeconomic status (SES) at higher risk of dying prematurely. Alcohol consumption has been shown to be a factor contributing to socioeconomic differences in mortality. However, little evidence is available from low- and middle-income countries. The objective of this study was to quantify mortality attributable to alcohol consumption in the adult (15+ years) general population of South Africa in 2015 by SES, age, and sex. A comparative risk assessment was performed using individual and aggregate data from South Africa and risk relations reported in the literature. Alcohol-attributable fractions (AAFs) and alcohol-attributable mortality rates were estimated for cause-specific mortality by SES, sex, and age. Monte Carlo simulation techniques were used to calculate 95% uncertainty intervals (UI). Overall, approximately 62,300 (95% UI 27,000-103,000) adults died from alcohol-attributable causes in South Africa in 2015, with 60% of deaths occurring in people in the low and 15% in the high SES groups. Age-standardized, alcohol-attributable mortality rates per 100,000 adults were highest for the low SES group (727 deaths, 95% UI 354-1208 deaths) followed by the middle (377 deaths, 95% UI 165-687 deaths) and high SES groups (163 deaths, 95% UI 71-289 deaths). The socioeconomic differences were highest for mortality from infectious diseases. People of low SES had a lower prevalence of current alcohol use but heavier drinking patterns among current drinkers. Among men, AAFs were elevated at low and middle SES, particularly for the middle and higher age groups (35+). Among women, AAFs differed less across SES groups and, in the youngest age group (15-34), women of high SES had elevated AAFs. Alcohol use contributed to vast socioeconomic differences in mortality. Where observed, elevated AAFs for people of low and middle SES arose from higher levels of consumption among current drinkers and not from the prevalence of current alcohol use per se. The findings can direct preventive measures and interventions on those at highest risk. Future research is needed to investigate socioeconomic differences in the risk functions relating alcohol use to cause-specific mortality.

Twitter Demographics

The data shown below were collected from the profiles of 20 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 146 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 146 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 14%
Researcher 14 10%
Student > Bachelor 14 10%
Student > Ph. D. Student 12 8%
Student > Postgraduate 7 5%
Other 26 18%
Unknown 52 36%
Readers by discipline Count As %
Medicine and Dentistry 32 22%
Nursing and Health Professions 9 6%
Social Sciences 9 6%
Psychology 7 5%
Agricultural and Biological Sciences 6 4%
Other 26 18%
Unknown 57 39%

Attention Score in Context

This research output has an Altmetric Attention Score of 126. 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 16 September 2022.
All research outputs
#278,318
of 22,869,263 outputs
Outputs from BMC Medicine
#235
of 3,438 outputs
Outputs of similar age
#6,943
of 328,226 outputs
Outputs of similar age from BMC Medicine
#8
of 62 outputs
Altmetric has tracked 22,869,263 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,438 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one has done particularly well, scoring higher than 93% 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 328,226 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 97% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.