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Multiple risk factor interventions for primary prevention of cardiovascular disease in low- and middle-income countries

Overview of attention for article published in Cochrane database of systematic reviews, August 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
9 tweeters
facebook
1 Facebook page
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

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41 Dimensions

Readers on

mendeley
273 Mendeley
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Title
Multiple risk factor interventions for primary prevention of cardiovascular disease in low- and middle-income countries
Published in
Cochrane database of systematic reviews, August 2015
DOI 10.1002/14651858.cd011163.pub2
Pubmed ID
Authors

Olalekan A Uthman, Louise Hartley, Karen Rees, Fiona Taylor, Shah Ebrahim, Aileen Clarke

Abstract

In many low- and middle-income countries (LMICs) morbidity and mortality associated with cardiovascular diseases (CVDs) have grown exponentially over recent years. It is estimated that about 80% of CVD deaths occur in LMICs. People in LMICs are more exposed to cardiovascular risk factors such as tobacco, and often do not have access to effective and equitable healthcare services (including early detection services). Evidence from high-income countries indicates that multiple risk factor intervention programmes do not result in reductions in CVD events. Given the increasing incidence of CVDs and lower CVD health awareness in LMICs it is possible that such programmes may have beneficial effects. To determine the effectiveness of multiple risk factor interventions (with or without pharmacological treatment) aimed at modifying major cardiovascular risk factors for the primary prevention of CVD in LMICs. We searched (from inception to 27 June 2014) the Cochrane Library (CENTRAL, HTA, DARE, EED), MEDLINE, EMBASE, Global Health and three other databases on 27 June 2014. We also searched two clinical trial registers and conducted reference checking to identify additional studies. We applied no language limits. We included randomised controlled trials (RCTs) of health promotion interventions to achieve behaviour change (i.e. smoking cessation, dietary advice, increasing activity levels) with or without pharmacological treatments, which aim to alter more than one cardiovascular risk factor (i.e. diet, reduce blood pressure, smoking, total blood cholesterol or increase physical activity) of at least six months duration of follow-up conducted in LMICs. Two authors independently assessed trial eligibility and risk of bias, and extracted data. We combined dichotomous data using risk ratios (RRs) and continuous data using mean differences (MDs), and presented all results with a 95% confidence interval (CI). The primary outcome was combined fatal and non-fatal cardiovascular disease events. Thirteen trials met the inclusion criteria and are included in the review. All studies had at least one domain with unclear risk of bias. Some studies were at high risk of bias for random sequence generation (two trials), allocation concealment (two trials), blinding of outcome assessors (one trial) and incomplete outcome data (one trial). Duration and content of multiple risk factor interventions varied across the trials. Two trials recruited healthy participants and the other 11 trials recruited people with varying risks of CVD, such as participants with known hypertension and type 2 diabetes. Only one study reported CVD outcomes and multiple risk factor interventions did not reduce the incidence of cardiovascular events (RR 0.57, 95% CI 0.11 to 3.07, 232 participants, low-quality evidence); the result is imprecise (a wide confidence interval and small sample size) and makes it difficult to draw a reliable conclusion. None of the included trials reported all-cause mortality. The pooled effect indicated a reduction in systolic blood pressure (MD -6.72 mmHg, 95% CI -9.82 to -3.61, I² = 91%, 4868 participants, low-quality evidence), diastolic blood pressure (MD -4.40 mmHg, 95% CI -6.47 to -2.34, I² = 92%, 4701 participants, low-quality evidence), body mass index (MD -0.76 kg/m², 95% CI -1.29 to -0.22, I² = 80%, 2984 participants, low-quality evidence) and waist circumference (MD -3.31, 95% CI -4.77 to -1.86, I² = 55%, 393 participants, moderate-quality evidence) in favour of multiple risk factor interventions, but there was substantial heterogeneity. There was insufficient evidence to determine the effect of these interventions on consumption of fruit or vegetables, smoking cessation, glycated haemoglobin, fasting blood sugar, high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL) cholesterol and total cholesterol. None of the included trials reported on adverse events. Due to the limited evidence currently available, we can draw no conclusions as to the effectiveness of multiple risk factor interventions on combined CVD events and mortality. There is some evidence that multiple risk factor interventions may lower blood pressure levels, body mass index and waist circumference in populations in LMIC settings at high risk of hypertension and diabetes. There was considerable heterogeneity between the trials, the trials were small, and at some risk of bias. Larger studies with longer follow-up periods are required to confirm whether multiple risk factor interventions lead to reduced CVD events and mortality in LMIC settings.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 273 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 <1%
Tanzania, United Republic of 1 <1%
Unknown 271 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 58 21%
Researcher 34 12%
Student > Ph. D. Student 32 12%
Student > Bachelor 28 10%
Student > Postgraduate 21 8%
Other 60 22%
Unknown 40 15%
Readers by discipline Count As %
Medicine and Dentistry 115 42%
Nursing and Health Professions 40 15%
Social Sciences 17 6%
Psychology 15 5%
Sports and Recreations 6 2%
Other 31 11%
Unknown 49 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 31 January 2017.
All research outputs
#1,645,303
of 12,527,219 outputs
Outputs from Cochrane database of systematic reviews
#3,964
of 8,923 outputs
Outputs of similar age
#38,227
of 238,215 outputs
Outputs of similar age from Cochrane database of systematic reviews
#131
of 245 outputs
Altmetric has tracked 12,527,219 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,923 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.2. This one has gotten more attention than average, scoring higher than 63% 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 238,215 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 245 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.