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The contribution of risk factors to socioeconomic inequalities in multimorbidity across the lifecourse: a longitudinal analysis of the Twenty-07 cohort

Overview of attention for article published in BMC Medicine, August 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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1 policy source
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58 X users
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1 Facebook page

Citations

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112 Dimensions

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216 Mendeley
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Title
The contribution of risk factors to socioeconomic inequalities in multimorbidity across the lifecourse: a longitudinal analysis of the Twenty-07 cohort
Published in
BMC Medicine, August 2017
DOI 10.1186/s12916-017-0913-6
Pubmed ID
Authors

Srinivasa Vittal Katikireddi, Kathryn Skivington, Alastair H. Leyland, Kate Hunt, Stewart W Mercer

Abstract

Multimorbidity is a major challenge to health systems globally and disproportionately affects socioeconomically disadvantaged populations. We examined socioeconomic inequalities in developing multimorbidity across the lifecourse and investigated the contribution of five behaviour-related risk factors. The Twenty-07 study recruited participants aged approximately 15, 35, and 55 years in 1987 and followed them up over 20 years. The primary outcome was development of multimorbidity (2+ health conditions). The relationship between five different risk factors (smoking, alcohol consumption, diet, body mass index (BMI), physical activity) and the development of multimorbidity was assessed. Social patterning in the development of multimorbidity based on two measures of socioeconomic status (area-based deprivation and household income) was then determined, followed by investigation of potential mediation by the five risk factors. Multilevel logistic regression models and predictive margins were used for statistical analyses. Socioeconomic inequalities in multimorbidity were quantified using relative indices of inequality and attenuation assessed through addition of risk factors. Multimorbidity prevalence increased markedly in all cohorts over the 20 years. Socioeconomic disadvantage was associated with increased risk of developing multimorbidity (most vs least deprived areas: odds ratio (OR) 1.46, 95% confidence interval (CI) 1.26-1.68), and the risk was at least as great when assessed by income (OR 1.53, 95% CI 1.25-1.87) or when defining multimorbidity as 3+ conditions. Smoking (current vs never OR 1.56, 1.36-1.78), diet (no fruit/vegetable consumption in previous week vs consumption every day OR 1.57, 95% CI 1.33-1.84), and BMI (morbidly obese vs healthy weight OR 1.88, 95% CI 1.42-2.49) were strong independent predictors of developing multimorbidity. A dose-response relationship was observed with number of risk factors and subsequent multimorbidity (3+ risk factors vs none OR 1.91, 95% CI 1.57-2.33). However, the five risk factors combined explained only 40.8% of socioeconomic inequalities in multimorbidity development. Preventive measures addressing known risk factors, particularly obesity and smoking, could reduce the future multimorbidity burden. However, major socioeconomic inequalities in the development of multimorbidity exist even after taking account of known risk factors. Tackling social determinants of health, including holistic health and social care, is necessary if the rising burden of multimorbidity in disadvantaged populations is to be redressed.

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X Demographics

The data shown below were collected from the profiles of 58 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 216 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 216 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 19%
Student > Master 35 16%
Researcher 30 14%
Student > Bachelor 20 9%
Student > Doctoral Student 11 5%
Other 23 11%
Unknown 56 26%
Readers by discipline Count As %
Medicine and Dentistry 53 25%
Nursing and Health Professions 26 12%
Social Sciences 24 11%
Psychology 12 6%
Agricultural and Biological Sciences 6 3%
Other 30 14%
Unknown 65 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 39. 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 11 June 2019.
All research outputs
#986,976
of 24,417,958 outputs
Outputs from BMC Medicine
#685
of 3,765 outputs
Outputs of similar age
#20,700
of 321,173 outputs
Outputs of similar age from BMC Medicine
#13
of 52 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,765 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 45.0. This one has done well, scoring higher than 81% 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 321,173 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 93% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.