Cardiovascular disease (CVD) presents a significant burden to the UK. This review presents data from nationally representative datasets to provide up-to-date statistics on mortality, prevalence, ...treatment and costs. Data focus on CVD as a whole, coronary heart disease (International Classification of Diseases (ICD):I20-25) and cerebrovascular disease (ICD:I60-69); however, where available, other cardiovascular conditions are also presented. In 2012, CVD was the most common cause of death in the UK for women (28% of all female deaths), but not for men, where cancer is now the most common cause of death (32% of all male deaths). Mortality from CVD varies widely throughout the UK, with the highest age-standardised CVD death rates in Scotland (347/100 000) and the North of England (320/100 000 in the North West). Prevalence of coronary heart disease is also highest in the North of England (4.5% in the North East) and Scotland (4.3%). Overall, around three times as many men have had a myocardial infarction compared with women. Treatment for CVD is increasing over time, with prescriptions and operations for CVD having substantially increased over the last two decades. The National Health Service in England spent around £6.8 billion on CVD in 2012/2013, the majority of which came from spending on secondary care. Despite significant declines in mortality in the UK, CVD remains a considerable burden, both in terms of health and costs. Both primary and secondary prevention measures are necessary to reduce both the burden of CVD and inequalities in CVD mortality and prevalence.
Summary Background Non-communicable diseases are the leading global cause of death and disproportionately afflict those living in low-income and lower-middle-income countries (LLMICs). The ...association between socioeconomic status and non-communicable disease behavioural risk factors is well established in high-income countries, but it is not clear how behavioural risk factors are distributed within LLMICs. We aimed to systematically review evidence on the association between socioeconomic status and harmful use of alcohol, tobacco use, unhealthy diets, and physical inactivity within LLMICs. Methods We searched 13 electronic databases, including Embase and MEDLINE, grey literature, and reference lists for primary research published between Jan 1, 1990, and June 30, 2015. We included studies from LLMICs presenting data on multiple measures of socioeconomic status and tobacco use, alcohol use, diet, and physical activity. No age or language restrictions were applied. We excluded studies that did not allow comparison between more or less advantaged groups. We used a piloted version of the Cochrane Effective Practice and Organisation of Care Group data collection checklist to extract relevant data at the household and individual level from the included full text studies including study type, methods, outcomes, and results. Due to high heterogeneity, we used a narrative approach for data synthesis. We used descriptive statistics to assess whether the prevalence of each risk factor varied significantly between members of different socioeconomic groups. The study protocol is registered with PROSPERO, number CRD42015026604. Findings After reviewing 4242 records, 75 studies met our inclusion criteria, representing 2 135 314 individuals older than 10 years from 39 LLMICs. Low socioeconomic groups were found to have a significantly higher prevalence of tobacco and alcohol use than did high socioeconomic groups. These groups also consumed less fruit, vegetables, fish, and fibre than those of high socioeconomic status. High socioeconomic groups were found to be less physically active and consume more fats, salt, and processed food than individuals of low socioeconomic status. While the included studies presented clear patterns for tobacco use and physical activity, heterogeneity between dietary outcome measures and a paucity of evidence around harmful alcohol use limit the certainty of these findings. Interpretation Despite significant heterogeneity in exposure and outcome measures, clear evidence shows that the burden of behavioural risk factors is affected by socioeconomic position within LLMICs. Governments seeking to meet Sustainable Development Goal (SDG) 3.4—reducing premature non-communicable disease mortality by a third by 2030—should leverage their development budgets to address the poverty-health nexus in these settings. Our findings also have significance for health workers serving these populations and policy makers tasked with preventing and controlling the rise of non-communicable diseases. Funding WHO.
Vegan diets, where animal- and all their by-products are excluded from the diet, have gained popularity, especially in the last decade. However, the evaluation of this type of diet has not been well ...addressed in the scientific literature. This study aimed to investigate the adequacy of vegan diets in European populations and of their macro- and micronutrient intakes compared to World Health Organization recommendations.
A systematic search in PubMed, Web of Science, IBSS, Cochrane library and Google Scholar was conducted and 48 studies (12 cohorts and 36 cross-sectional) were included.
Regarding macronutrients, vegan diets are lower in protein intake compared with all other diet types. Veganism is also associated with low intake of vitamins B2, Niacin (B3), B12, D, iodine, zinc, calcium, potassium, selenium. Vitamin B12 intake among vegans is significantly lower (0.24–0.49 μg, recommendations are 2.4 μg) and calcium intake in the majority of vegans was below recommendations (750 mg/d). No significant differences in fat intake were observed. Vegan diets are not related to deficiencies in vitamins A, B1, Β6, C, E, iron, phosphorus, magnesium, copper and folate and have a low glycemic load.
Following a vegan diet may result in deficiencies in micronutrients (vitamin B12, zinc, calcium and selenium) which should not be disregarded. However, low micro- and macronutrient intakes are not always associated with health impairments. Individuals who consume a vegan diet should be aware of the risk of potential dietary deficiencies.
Non-communicable diseases (NCDs) are the leading cause of death globally. Eighty-two percent of premature NCD deaths occur within low- and lower middle-income countries (LLMICs). Research to date, ...largely drawn from high-income countries, suggests that disadvantaged and marginalized groups have a higher NCD burden, but there has been a dearth of research studying this relationship within LLMICs. The purpose of this systematic review is to map the literature on evidence from LLMICs on the socio-economic status (SES) gradient of four particular NCDs: cardiovascular disease, cancer, diabetes, and chronic respiratory diseases.
We conducted a comprehensive literature search for primary research published between 1 January 1990 and 27 April 2015 using six bibliographic databases and web resources. We included studies that reported SES and morbidity or mortality from cardiovascular disease, cancer, diabetes and chronic respiratory diseases within LLMICs.
Fifty-seven studies from 17 LLMICs met our inclusion criteria. Fourteen of the 18 papers that reported significant associations between cancer and SES suggested that low SES groups had the highest cancer risk. Eleven of 15 papers reporting significant relationships between CVD and SES suggested that low SES groups have higher risk. In contrast, seven of 12 papers reporting significant findings related to diabetes found that higher SES groups had higher diabetes risk. We identified just three studies on the relationship between chronic respiratory diseases and SES; none of them reported significant findings.
Only 17 of the 84 LLMICs were represented, highlighting the need for more research on NCDs within these countries. The majority of studies were medium to high quality cross-sectional studies. When we restricted our analyses to high quality studies only, for both cancer and cardiovascular disease more than half of studies found a significantly higher risk for those of lower SES. The opposite was true for diabetes, whilst there was a paucity of high quality research on chronic respiratory disease. Development programmes must consider health alongside other aims and NCD prevention interventions must target all members of the population.
Prospero: CRD42015020169.
Non-communicable diseases (NCDs) disproportionately affect low- and lower-middle income countries (LLMICs) where 80% of global NCD related deaths occur. LLMICs are the primary focus of interventions ...to address development and poverty indicators. We aimed to synthesise the evidence of these interventions' impact on the four primary NCDs (cardiovascular disease, diabetes, chronic respiratory disease and cancer) and their common behavioural risk factors (unhealthy diets, physical inactivity, tobacco and alcohol use).
We systematically searched four online databases (Medline, Embase, Web of Science and Global Health) for primary research conducted in LLMICS, published between January 1st 1990 and February 15th 2016. Studies involved development or poverty interventions which reported on outcomes relating to NCDs. We extracted summary level data on study design, population, health outcomes and potential confounders.
From 6383 search results, 29 studies from 24 LLMICs published between 1999 and 2015 met our inclusion criteria. The quality of included studies was limited and heterogeneity of outcome measures required narrative synthesis. One study measured impact on NCD prevalence, one physical activity and 27 dietary components. The majority of papers (23), involved agricultural interventions. Primary outcome measures tended to focus on undernutrition. Intensive agricultural interventions were associated with improved calorie, vitamin, fruit and vegetable intake. However, positive impacts were reliant on participant's land ownership, infection status and limited in generalisability. Just three studies measured adult obesity; two indicated increased income and consequential food affordability had the potential to increase obesity. Overall, there was poor alignment between included studies outcome measures and the key policy options and objectives of the Global Action Plan on NCDs.
Though many interventions addressing poverty and development have great potential to impact on NCD prevalence and risk, most fail to measure or report these outcomes. Current evidence is limited to behavioural risk factors, namely diet and suggests a positive impact of agricultural-based food security programmes on dietary indicators. However, studies investigating the impact of improved income on obesity tend to show an increased risk. Embedding NCD impact evaluation into development programmes is crucial in the context of the Sustainable Development Goals and the rapid epidemiological transitions facing LLMICs.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
Self-reported measures of tobacco use may have limited validity, particularly among some populations. This study aims to validate self-reported smoking measures among Georgian ...adults participating in the 2016 STEPS survey using cotinine biomarker measurements, and to explore potential differences according to sociodemographic characteristics. Additionally, this paper examines how the estimated prevalence of smoking in the population varies according to measurement type.
Methods
Using the WHO standardized STEPS methodology, adults self-reported their smoking status. In a later stage of the survey, a subset of participants provided a urine sample, which was tested for cotinine. Using each participant’s objective cotinine measurement and their self-reported smoking status, we calculated the sensitivity, specificity and positive predictive value of self-reported smoking. Next, we calculated the estimated prevalence of smokers according to the type of measurement.
Results
Results indicated high sensitivity (83.37%, 95% CI: 76.79–88.37%) among males and relatively low sensitivity (38.60% CI: 29.23–48.90%) among females. According to self-report, the prevalence of smokers was 26.44% (23.61–29.48%), while according to cotinine detection, the prevalence of smokers was 32.27% (29.16–35.55%). Among all subgroups, the self-reported prevalence of smoking was significantly lower than the cotinine-detected prevalence.
Conclusions
To the best of our knowledge, this is the first time that the validity of the STEPS self-reported tobacco indicator has been tested. Self-reported measures of smoking status may lead to an under-estimation of smoking prevalence among Georgian adults, especially women. These findings suggest that integration of biochemical measures of smoking into tobacco use studies may be an important investment.
Researchers and policy-makers are interested in the influence that food retailing around schools may have on child obesity risk. Most previous research comes from North America, uses data aggregated ...at the school-level and focuses on associations between fast food outlets and school obesity rates. This study examines associations between food retailing and BMI among a large sample of primary school students in Berkshire, England. By controlling for individual, school and home characteristics and stratifying results across the primary school years, we aimed to identify if the food environment around schools had an effect on BMI, independent of socio-economic variables.
We measured the densities of fast food outlets and food stores found within schoolchildren's home and school environments using Geographic Information Systems (GIS) and data from local councils. We linked these data to measures from the 2010/11 National Child Measurement Programme and used a cross-classified multi-level approach to examine associations between food retailing and BMI z-scores. Analyses were stratified among Reception (aged 4-5) and Year 6 (aged 10-11) students to measure associations across the primary school years.
Our multilevel model had three levels to account for individual (n = 16,956), home neighbourhood (n = 664) and school (n = 268) factors. After controlling for confounders, there were no significant associations between retailing near schools and student BMI, but significant positive associations between fast food outlets in home neighbourhood and BMI z-scores. Year 6 students living in areas with the highest density of fast food outlets had an average BMI z-score that was 0.12 (95% CI: 0.04, 0.20) higher than those living in areas with none.
We found little evidence to suggest that food retailing around schools influences student BMI. There is some evidence to suggest that fast food outlet densities in a child's home neighbourhood may have an effect on BMI, particularly among girls, but more research is needed to inform effective policies targeting the effects of the retail environment on child obesity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
BackgroundNon-communicable diseases (NCDs) are the leading cause of death and disability worldwide, with low-income and middle-income countries experiencing a disproportionately high burden. Since ...2010 WHO has promoted 24 highly cost-effective interventions for NCDs, dubbed ‘best buys’. It is unclear whether these interventions have been evaluated in low-income and lower-middle-income countries (LLMICs).AimTo systematically review research on interventions aligned to WHO ‘best buys’ for NCDs in LLMICs.MethodsWe searched 13 major databases and included papers conducted in the 83 World Bank-defined LLMICs, published between 1 January 1990 and 5 February 2015. Two reviewers independently screened papers and assessed risk of bias. We adopted a narrative approach to data synthesis. The primary outcomes were NCD-related mortality and morbidity, and risk factor prevalence.ResultsWe identified 2672 records, of which 36 were included (608 940 participants). No studies on ‘best buys’ were found in 89% of LLMICs. Nineteen of the 36 studies reported on the effectiveness of tobacco-related ‘best buys’, presenting good evidence for group interventions in reducing tobacco use but weaker evidence for interventions targeting individuals. There were fewer studies on smoking bans, warning labels and mass media campaigns, and no studies on taxes or marketing restrictions. There was supportive evidence that cervical screening and hepatitis B immunisation prevent cancer in LLMICs. A single randomised controlled trial supported polypharmacy for cardiovascular disease. Fourteen of the ‘best buy’ interventions did not have any good evidence for effectiveness in LLMICs.ConclusionsWe found studies on only 11 of the 24 interventions aligned with the WHO ‘best buys’ from LLMIC settings. Most LLMICs have not conducted research on these interventions in their populations. LLMICs should take action to implement and evaluate ‘best buys’ in their national context, based on national priorities, and starting with interventions with the strongest evidence base.
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