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      Polyunsaturated fatty acids for the primary and secondary prevention of cardiovascular disease

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          Abstract

          Evidence on the health effects of total polyunsaturated fatty acids (PUFA) is equivocal. Fish oils are rich in omega‐3 PUFA and plant oils in omega‐6 PUFA. Evidence suggests that increasing PUFA‐rich foods, supplements or supplemented foods can reduce serum cholesterol, but may increase body weight, so overall cardiovascular effects are unclear. To assess effects of increasing total PUFA intake on cardiovascular disease and all‐cause mortality, lipids and adiposity in adults. We searched CENTRAL, MEDLINE and Embase to April 2017 and clinicaltrials.gov and the World Health Organization International Clinical Trials Registry Platform to September 2016, without language restrictions. We checked trials included in relevant systematic reviews. We included randomised controlled trials (RCTs) comparing higher with lower PUFA intakes in adults with or without cardiovascular disease that assessed effects over 12 months or longer. We included full texts, abstracts, trials registry entries and unpublished data. Outcomes were all‐cause mortality, cardiovascular disease mortality and events, risk factors (blood lipids, adiposity, blood pressure), and adverse events. We excluded trials where we could not separate effects of PUFA intake from other dietary, lifestyle or medication interventions. Two review authors independently screened titles and abstracts, assessed trials for inclusion, extracted data, and assessed risk of bias. We wrote to authors of included trials for further data. Meta‐analyses used random‐effects analysis, sensitivity analyses included fixed‐effects and limiting to low summary risk of bias. We assessed GRADE quality of evidence. We included 49 RCTs randomising 24,272 participants, with duration of one to eight years. Eleven included trials were at low summary risk of bias, 33 recruited participants without cardiovascular disease. Baseline PUFA intake was unclear in most trials, but 3.9% to 8% of total energy intake where reported. Most trials gave supplemental capsules, but eight gave dietary advice, eight gave supplemental foods such as nuts or margarine, and three used a combination of methods to increase PUFA. Increasing PUFA intake probably has little or no effect on all‐cause mortality (risk 7.8% vs 7.6%, risk ratio (RR) 0.98, 95% confidence interval (CI) 0.89 to 1.07, 19,290 participants in 24 trials), but probably slightly reduces risk of coronary heart disease events from 14.2% to 12.3% (RR 0.87, 95% CI 0.72 to 1.06, 15 trials, 10,076 participants) and cardiovascular disease events from 14.6% to 13.0% (RR 0.89, 95% CI 0.79 to 1.01, 17,799 participants in 21 trials), all moderate‐quality evidence. Increasing PUFA may slightly reduce risk of coronary heart disease death (6.6% to 6.1%, RR 0.91, 95% CI 0.78 to 1.06, 9 trials, 8810 participants) and stroke (1.2% to 1.1%, RR 0.91, 95% CI 0.58 to 1.44, 11 trials, 14,742 participants, though confidence intervals include important harms), but has little or no effect on cardiovascular mortality (RR 1.02, 95% CI 0.82 to 1.26, 16 trials, 15,107 participants) all low‐quality evidence. Effects of increasing PUFA on major adverse cardiac and cerebrovascular events and atrial fibrillation are unclear as evidence is of very low quality. Increasing PUFA intake slightly reduces total cholesterol (mean difference (MD) ‐0.12 mmol/L, 95% CI ‐0.23 to ‐0.02, 26 trials, 8072 participants) and probably slightly decreases triglycerides (MD ‐0.12 mmol/L, 95% CI ‐0.20 to ‐0.04, 20 trials, 3905 participants), but has little or no effect on high‐density lipoprotein ( HDL) (MD ‐0.01 mmol/L, 95% CI ‐0.02 to 0.01, 18 trials, 4674 participants) or low‐density lipoprotein ( LDL) (MD ‐0.01 mmol/L, 95% CI ‐0.09 to 0.06, 15 trials, 3362 participants). Increasing PUFA probably causes slight weight gain (MD 0.76 kg, 95% CI 0.34 to 1.19, 12 trials, 7100 participants). Effects of increasing PUFA on serious adverse events such as pulmonary embolism and bleeding are unclear as the evidence is of very low quality. This is the most extensive systematic review of RCTs conducted to date to assess effects of increasing PUFA on cardiovascular disease, mortality, lipids or adiposity. Increasing PUFA intake probably slightly reduces risk of coronary heart disease and cardiovascular disease events, may slightly reduce risk of coronary heart disease mortality and stroke (though not ruling out harms), but has little or no effect on all‐cause or cardiovascular disease mortality. The mechanism may be via lipid reduction, but increasing PUFA probably slightly increases weight. Review question We reviewed randomised trials (participants have an equal chance to be assigned to either treatment) examining effects of increasing intake of polyunsaturated fatty acids (PUFA) on deaths and diseases of the heart and circulation (cardiovascular diseases), including heart attacks and stroke. Background We eat PUFA in our usual food, but quantities of PUFA eaten vary. There is some evidence that increasing the amount of PUFA we eat can reduce our blood cholesterol and make us less likely to develop cardiovascular disease, particularly if PUFAs are eaten instead of saturated fats (fats from animal sources such as meat and cheese). But eating more PUFA may increase our body weight, and omega‐6 fats (one component of PUFA) may worsen cardiovascular risk by increasing inflammation. Evidence on the benefits or harms of increasing PUFA intake on diseases of the heart and circulation, or on other health outcomes, is inconclusive. Trial characteristics Evidence in this Cochrane Review is current to 27 April 2017. We included 49 trials randomising 24,272 participants, for one to eight years. These trials assessed effects of eating more, compared to less PUFA, on diseases of the heart and circulation, and deaths. Twelve trials were very trustworthy (had low risk of bias overall). Participants were men and women, some with existing illnesses and some not. Trials took place in North America, Asia, Europe and Australia, and sixteen were funded only by national or charitable agencies. Key results Increasing PUFA probably makes little or no difference (neither benefit nor harm) to our risk of death (moderate‐quality evidence), and may make little or no difference to our risk of dying from cardiovascular disease (low‐quality evidence). However, increasing PUFA probably slightly reduces our risk of heart disease events and of combined heart and stroke events (moderate‐quality evidence). Fifty three people would need to eat more PUFA to prevent one person experiencing a heart disease event, and 63 people to prevent one person experiencing a heart or stroke event. Increasing PUFA may very slightly reduce risk of death due to heart disease, as well as stroke, but harm is possible (low‐quality evidence). PUFA probably slightly reduces fats circulating in the blood (cholesterol, high‐quality evidence and triglycerides, moderate‐quality evidence). Increasing PUFA probably slightly increases body weight (moderate‐quality evidence). The evidence mainly comes from trials of men living in high‐income countries.

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              Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

              Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45-54% since 1990; ischaemic heart disease and stroke YLLs increased by 17-28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Cochrane Database of Systematic Reviews
                Wiley
                14651858
                July 18 2018
                Affiliations
                [1 ]University of East Anglia; Norwich Medical School; Norwich Research Park Norwich Norfolk UK NR4 7TJ
                [2 ]University College London; Institute of Health Informatics Research; 222 Euston Road London UK NW1 2DA
                [3 ]University of East Anglia; School of Health Sciences; Edith Cavell Building Norwich UK NR4 7TJ
                Article
                10.1002/14651858.CD012345.pub2
                b7b3dc42-67cb-4e71-ae15-c3b73976a7d0
                © 2018
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