Olive oil and wholegrains 'lower heart disease risk'

Tuesday September 29 2015

Butter is high in saturated fat

"Butter isn't better than margarine after all," declares the Mail Online, after a new study found reducing saturated fat does indeed lower the risk of heart disease.

The study, which followed the dietary habits of nearly 130,000 people over almost 30 years, found those who had a diet high in unsaturated fats, such as olive oil, and wholegrains had a lower risk of heart disease.

The findings, published in the Journal of the American College of Cardiology, showed replacing 5% of saturated fats in the diet with unsaturated fats reduced the risk of coronary heart disease (CHD) by 25%.

Recent studies have cast doubt on the link between saturated fat intake and the risk of developing CHD. Researchers did not find a link between eating less saturated fat and a lower death rate.

The authors of the study claim this is because many people who cut down on saturated fats replace it with added sugar and refined carbohydrates, such as potatoes and white bread, which are equally unhealthy.

Overall, the study suggests consuming higher amounts of unsaturated fats and wholegrains was associated with a lower risk of developing heart disease.

But although the study included a large sample size and long follow-up period, it cannot prove causality. There is the possibility people didn't accurately recall their diet, and other health and lifestyle factors could be influencing any observed link.

And the results of this study cannot apply to the whole population – it only included health professionals, who may have distinct health and lifestyle characteristics.

Nevertheless, it is advisable to follow a healthy lifestyle, taking regular exercise and eating a balanced diet that includes complex carbohydrates like wholegrains, and is low in saturated fat, salt and sugar.

While the study does not show saturated fats should be avoided altogether, it perhaps supports the well-known adage "everything in moderation". 

Where did the story come from?

The study was carried out by researchers from Harvard Medical School and the Wellness Institute at Cleveland Clinic, and was funded by the US National Institutes of Health.

It was published in the peer-reviewed Journal of the American College of Cardiology.

The UK media reported the findings of the study accurately, but some of the strengths and weaknesses were not explicitly mentioned.

The Mail reports a quote from one of the lead authors of the study, Professor Frank Hu, who said: "Our research does not exonerate saturated fat. In terms of heart disease risk, saturated fat and refined carbohydrates appear to be similarly unhealthy."

He adds: "Our findings suggest that when patients are making lifestyle changes to their diets, cardiologists should encourage the consumption of unsaturated fats like vegetable oils, nuts, and seeds, as well as healthy carbohydrates such as wholegrains". 

What kind of research was this?

This was an observational study that investigated the associations between saturated fat (such as butter, cheese and whipped cream) compared with the intake of unsaturated fat (such as vegetable oil, sunflower oil and walnuts) and different sources of carbohydrates, and the risk of developing heart disease.

Recent studies have cast doubt on the link between saturated fat intake and the risk of developing CHD. But researchers say these studies did not consider that when cutting down on saturated fat, people tended to replace it with carbohydrates from added sugars and refined starches, such as potatoes, white bread and pasta, which did not reduce their CHD risk.

This type of study, involving many people over many years, can show an association between eating less saturated fat and a reduced CHD risk. But it cannot show causality, as many other factors may be involved, including the participants' ability to accurately remember their diet.

What did the research involve?

This study included 84,628 women from the Nurses' Health Study (aged 30 to 55 at enrolment) and 42,908 men from the Health Professionals Follow-up Study (aged 40 to 75 at enrolment). These individuals were free from diabetes, cardiovascular disease and cancer at the start of the study.

Participants completed a food frequency questionnaire once every four years throughout the study period. They were asked what type of fat oil they used for frying and baking, and if they used any margarine during the past year. The questionnaire had nine possible responses, ranging from "never" to "less than once per month", to "more than six times per day".

Daily fat intake by type was calculated by multiplying the frequency of the food consumption with its nutrient content using US Department of Agriculture food composition data.

In the study, carbohydrates were classed as either wholegrains or refined starches, added sugars, refined grains, and sugary foods and drinks.

The outcomes of interest were non-fatal heart attack, heart disease overall, and deaths as a result of heart disease, which were identified through a review of medical records.

What were the basic results?

Over a follow-up period of 24 to 30 years, there were 7,667 cases of heart disease (4,931 non-fatal heart attacks and 2,736 deaths from heart disease).

Some of the main findings of the study are listed below:

• Highest intake of unsaturated fats was associated with a 20% significantly lower risk of heart disease compared with individuals with the lowest unsaturated fats intake (hazard ratio [HR]: 0.80, 95% confidence interval [CI]: 0.73 to 0.88).
• Highest intake of carbohydrates from wholegrains was associated with a 10% significantly lower risk of heart disease compared with individuals with the lowest wholegrain intake (HR 0.90, 95% CI 0.83 to 0.98).
• There was a borderline significant trend for high intake of carbohydrates from refined or added sugars to be associated with increased risk of heart disease (HR 1.10, 95% CI 1.00 to 1.21).
• Replacing 5% of energy intake from saturated fats with equivalent energy intake from unsaturated fats, monounsaturated fatty acids, or carbohydrates from wholegrains was calculated to reduce the risk of heart disease by 25%, 15% and 9% respectively. 

How did the researchers interpret the results?

The researchers concluded unsaturated fats and high-quality carbohydrates, such as wholegrains, can be used to replace saturated fats to reduce CHD risk.

They said: "Unsaturated fats, such as those from vegetable oils, nuts, and seeds, should have an expanded role as a replacement for [saturated fats].

"However, our data from national surveys suggest that, when decreasing [saturated fats] intake, most people appear to increase the intake of low-quality carbohydrates, such as refined starches and/or added sugars, rather than increase the intake of unsaturated fats." 

Conclusion

This observational study looked for an association between saturated fat intake compared with unsaturated fat intake and complex carbohydrate intake, and the risk of developing heart diseases.

Overall, the study suggested consuming higher amounts of unsaturated fats and complex carbohydrates such as wholegrains was associated with a lower risk of developing heart disease.

This study has several strengths, such as the inclusion of a large sample size of both men and women, and a long follow-up period. But because of the observational study design, it cannot prove causality.

The researchers have adjusted their analyses for various health and lifestyle factors that could be influencing the link, such as body mass index (BMI), smoking status, physical activity and alcohol intake.

However, it is difficult to fully account for the influence of all of these factors – or others that were unmeasured – that could be involved in the diet and heart disease link.

Another important limitation is the possibility of recall bias. People were asked to specify by quantity the types of fat they used in baking and frying in the previous year, and the amount and types of carbohydrates they had eaten. It's possible some of this information may have been inaccurate, and some people could have been put into the wrong intake groups.

As the participants were all health professionals, they may have distinct health and lifestyle characteristics, meaning their results cannot be applied to the population as a whole.

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Fidgeting probably not a useful alternative to proper exercise

Thursday September 24 2015

Regular breaks from sitting are recommended

"Fidgeting 'offsets unhealthy effects of sitting for long periods and may help you live longer'," the Daily Mirror reports.

A new study reported fidgeting may help make up for the harmful effects of most people's sedentary lifestyles. Sitting down for most of the day has been linked to an increased risk of diabetes and heart disease.

A study following more than 10,000 women for 12 years found an association between high levels of self-reported fidgeting and reduced risk of death. This was despite them spending several hours a day sitting. 

But while the media reports fidgeting is therefore good for you, this study had major limitations and the results were mixed.

The women were asked to rate how much they fidget on a scale of 1 (none) to 10 (constantly) in a single questionnaire. Other details, such as activity level, amount of time sitting, occupation and diet, were also only collected at a single point in time. 

These estimates may be inaccurate, and each factor may have changed over the study period. This means we cannot be confident fidgeting reduces the negative effects associated with a sedentary lifestyle.

Going for a brisk walk, jog, or swim is almost certainly better for you than tapping your feet. Read more about the benefits of regular exercise. 

Where did the story come from?

The study was carried out by researchers from University College London, Heriot-Watt University, the University of Edinburgh, and the University of Leeds.

It was funded by the World Cancer Research Fund, the Biotechnology and Biological Sciences Research Council, and the Medical Research Council. No potential conflicts of interest were reported.

The study was published in the peer-reviewed American Journal of Preventive Medicine.

In general the UK media reported the findings of the study at face value, not mentioning any of the study's limitations.

The Guardian incorrectly described fidgeters as people whose "limbs tapped, wobbled and gently vibrated" or "colleagues who are constantly tapping their feet", but this was not how the questionnaire asked women to rate their level of fidgeting.  

What kind of research was this?

This cohort study followed more than 10,000 women over a period of 12 years to see if there was a link between fidgeting, the amount of time spent sitting, and risk of death.

Cohort studies like this are a good way of finding associations between environmental and lifestyle factors and outcomes because they can involve large numbers of participants and are done over a long period of time to capture the long-term effects of an exposure.

However, they cannot prove cause and effect, which would require a randomised controlled trial. Such a trial would be tricky to organise, however. 

What did the research involve?

The researchers analysed data on a sample of 10,937 women who participated in the United Kingdom Women's Cohort Study (UKWCS).

These women completed a sociodemographic and food frequency questionnaire at some point between 1995 and 1998. At that time they were aged between 35 and 69.

They completed a second questionnaire between 1999 and 2002, which included information on health behaviours, illness, 24-hour activity, physical activity and fidgeting.

Fidgeting was assessed on a scale from 1 to 10 using the question, "How much of your time do you spend fidgeting?". A score of 1 would mean "no fidgeting at all", with 10 indicating "constant fidgeting".

The women were followed up until December 2013. The results were analysed to look for an association between the level of self-reported fidgeting and risk of death.

The researchers adjusted the results to take into account the following possible confounding factors:

• age
• chronic disease
• physical activity level
• sitting time
• level of education
• occupational social class
• retirement status
• smoking status (current versus former or never)
• alcohol use
• fruit and vegetable consumption
• hours of sleep

The researchers performed additional analyses to see if body mass index (BMI) could account for the results seen. 

What were the basic results?

Women who reported the lowest fidgeting rate had a 30% increased risk of death from any cause if they sat for seven or more hours a day compared with less than five hours (hazard ratio [HR] 1.30, 95% confidence interval [CI] 1.02 to 1.66).

For women in the highest self-reported fidgeting group, sitting for five or six hours a day was associated with a 37% reduction in risk of death compared with sitting for less than five hours a day (HR 0.63, 95% CI 0.43 to 0.91).

Sitting for longer than six hours a day was not associated with an increased or decreased risk of death in this group.

The length of sitting time was not associated with risk of death in women classed as being in the middle group of fidgets. BMI did not alter the results. 

How did the researchers interpret the results?

The authors concluded that, "Fidgeting may reduce the risk of all-cause mortality associated with excessive sitting time." They called for "more detailed measures of fidgeting … to replicate these findings". 

Conclusion

This cohort study found fidgeting may reduce the risk of death associated with sitting for long periods of time. 

The study's strengths include the large number of participants, long follow-up period and attempts to account for a number of potential confounding factors.

However, the study is purely based on one self-reported estimate of most of these factors, which reduces confidence in the strength of the results. Fidgeting is largely an unconscious activity, so many people could have no accurate recall of how much or how little they fidget.

Not only could the estimates be unreliable, but many of these variables may have changed over the course of the 12 years of follow-up, such as activity level, diet, smoking and employment status.

The analyses did not consider whether the sitting was related to occupation, leisure time or watching TV, which may have influenced the results.

A further major limitation is in the assessment of the amount of fidgeting. Again, this was only assessed on one occasion through the women guessing how much they fidget on a scale of 1 to 10. This was not validated through any objective measurement or asking family, friends or colleagues to see if they agree. 

The researchers suggested future studies could try to address this limitation through combining the self-report with tri-axial accelerometers (movement sensing devices that people wear).

In conclusion, though interesting, the results of this study do not lead to a call for people to fidget more. Instead, the advice remains the same: stop smoking, drink alcohol within safe limits, eat a balanced diet that includes plenty of fresh fruit and vegetables, and keep physically active. 

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UK women's life expectancy 'second worst' in Western Europe

Wednesday September 23 2015

Europe is the booziest continent on the globe

"British women have second worst life expectancy in Europe," The Guardian reports. This is one of the findings of a Europe-wide health report carried out by the World Health Organization (WHO). The report also warned that European levels of alcohol consumption, smoking and obesity are alarmingly high, which could result in the following possibility: "Young Europeans may die at an earlier age than their grandparents".

In the interests of accuracy, we should point out that the claim British women have the second worst life expectancy in Europe is incorrect. This figure is based on an analysis of countries traditionally regarded as being part of Western Europe. Life expectancy figures in other parts of Europe, such as Russia and the Balkan states, are significantly lower than in the UK.

What is the basis of these reports?

The WHO has published its European Health Report, which measures progress against health targets for Europe, looking at how individual countries compare, and commenting on possible future threats to the health of the region. It publishes this regional report every three years.

What data did they look at?

The WHO looked at progress towards six targets for Europe. These were:

• to reduce premature mortality (early death)
• to increase life expectancy (how long people born now can expect to live)
• to reduce inequalities in the health of people across the European region
• to enhance wellbeing
• to move towards everyone in Europe having access to healthcare
• to establish individual targets for European countries

They reviewed statistics on death from:

• heart disease, stroke, cancers and respiratory diseases, such as chronic obstructive pulmonary disease (COPD)
• estimates of the life expectancy of male and female children today
• comparisons between different states of health outcomes
• measures of wellbeing
• lifestyle factors, such as tobacco smoking, alcohol consumption and obesity
• health policies in different countries

Many figures were based on estimates. For example, figures on tobacco and alcohol use are estimates by the WHO researchers, who applied trends in tobacco reduction from the period 2000-08 to national figures collected in 2010. The report authors say more up-to-date information had not been submitted by individual countries.

What are the main findings?

Despite the tone of the news coverage, the report is generally positive, showing that Europe is on track to achieving targets to reduce premature death from cardiovascular diseases, cancer, diabetes and lung diseases.

However, it says that most of the recent progress has been seen in the countries that had the worst health records, rather than countries like the UK, which were already doing relatively well.

The report warns that Europe has the highest rates of alcohol consumption and tobacco smoking in the world, with obesity rates second only to North America. The report authors warn that these lifestyle factors "are among the major public health problems" in Europe and that Europe is likely to miss a target to reduce tobacco use by 30% by 2025.

Looking at country-specific figures, the report says that people in the UK are much less likely to smoke (estimates are around 20%, compared to a European average of 30%). People in the UK drink, on average, 9-12 litres of pure alcohol a year (equivalent to around 100-130 bottles of wine), in line with the European average of 11 litres.

Rates of obesity and overweight are among the highest in Europe, with only Turkey and Andorra reporting more obese people.

The report showed life expectancy at birth has been rising in Europe since the 1990s and stood at 76.8 years in 2011 (the most recent date for which figures were available). Women live longer than men, with an average life expectancy of 73 for men and 80 for women. In the UK, the figures are 78.8 for men and 82.7 for women. While this is better than the European average, it puts life expectancy for UK women low on a WHO list of 15 benchmark Western European countries. Most of the figures for life expectancy for women on this list cluster around the 83- to 84-year mark, ranging from 82.1 in Denmark to 85.5 in Spain.

The media reports of British women's life expectancy being the "second lowest in Europe" does not reflect that this is based on a list of just 15 countries – not the whole of Europe. By contrast, life expectancy for women in Russia (which is not on the list) is just 75.

What does this mean for me?

If you compared this data to data from 100 years ago, a trend would become immediately obvious. In 1915, many Europeans would die of infection. Today, the biggest killers are what are known as non-communicable diseases (NCDs). These are non-infectious diseases such as lung cancer, heart disease and stroke, which are usually associated with lifestyle factors including obesity, smoking and alcohol consumption.

The report warns that NCDs are now the biggest threats to future health in Europe.

The good news is, while there is no room for complacency, UK rates of tobacco smoking are below the European average and continue to fall.

Alcohol consumption in the UK is in line with the rest of Europe – and Europeans are the biggest consumers of alcohol in the world. However, perhaps what is most worrying are the statistics on obesity and overweight, where the UK is among the worst in Europe.

The report says the figures on alcohol, tobacco and obesity are "alarmingly high" and acknowledges that individual countries have made progress in tackling them. Commenting on the report, the WHO warns that, while Europeans are living longer, these lifestyle factors "could mean that the life expectancy of future generations will fall". 

Ways you can reduce your risk of developing one or more NCDs include stopping smoking, drinking alcohol in moderation and maintaining a healthy weight through diet and exercise. These steps should also help keep your cholesterol and blood pressure at a healthy rate.

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Tai chi 'may help people cope better with diseases of ageing'

Monday September 21 2015

Tai chi is said to improve balance and flexibility

"Tai chi can help older patients with disabling conditions," The Guardian reports after an analysis of old data found the martial art may help relieve some symptoms of four age-related diseases: cancer, heart failure, osteoarthritis and chronic obstructive pulmonary disease (COPD).

Notable significant effects were seen, with improvements in walking for those who had heart failure, improved strength of the big quadriceps muscles for those with heart failure and COPD, and pain and stiffness for people with osteoarthritis. There were also trends for effects on depression and quality of life for those with heart failure and COPD.

However, this review can't prove tai chi will definitely have a positive effect for people who have these conditions. The trials were highly variable in their study population, the type of tai chi practised, the type of comparison intervention, and the outcomes examined. Despite the large collective number of studies, most of the individual results were based on only one or a few studies. 

Nevertheless, remaining active and exercising within your limits is positive in all stages of life, even for those who have a chronic disease. If you find tai chi enjoyable and it boosts your physical or mental wellbeing, that can only be a good thing.

If tai chi is not your cup of oolong, you could always try the Strength and Flex exercise plan. 

Where did the story come from?

The study was carried out by researchers from the University of British Columbia and the University of Toronto, and was funded by the University of British Columbia and the British Columbia Lung Association.

It was published in the peer-reviewed British Journal of Sports Medicine.

The UK media provide a generally accurate picture of the evidence. However, it would have been helpful to note that this study was limited by the highly variable studies the researchers looked at, which makes it difficult to form any definite conclusions.   

What kind of research was this?

This systematic review aimed to identify trials looking at the effectiveness of tai chi for four common chronic conditions: cancer, heart failure, COPD and osteoarthritis. The results of the identified trials were then pooled in a meta-analysis to give an overall effect.

Tai chi involves gentle flowing movements to improve strength, posture and balance, and has become an increasingly popular form of exercise, particularly among the middle-aged and elderly.

It has also been tried as a complementary healthcare approach for many different conditions, with some studies suggesting it has both physical and psychosocial benefits.

This review aimed to gather the evidence surrounding the martial art to get an overall conclusive summary of its effects. However, the results of a systematic review are only ever as good as the studies included, so there may be inherent limitations in the quality of the various studies and the methods used.   

What did the research involve?

The researchers searched four literature databases up to the end of December 2014 for randomised controlled trials published in English that compared tai chi with any other control group in people with four chronic conditions: cancer, heart failure, COPD and osteoarthritis. The studies were assessed for quality, and the outcomes were pooled for different disease-specific symptoms and outcomes.

33 studies met the inclusion criteria, but several reported data in two or more publications, giving a total of 24 individual trials. There were five studies available each for cancer, heart failure and COPD, and nine for osteoarthritis. The results of all the osteoarthritis studies, and four of the studies for each of the other conditions, were pooled in the meta-analysis.

The trials were of average quality, with most having a score of five out of 10 on the quality scale used (the PEDro scale). The sample size of the trials included ranged from 11 to 206. The average age of the participants varied, but they tended to be in their 60s and 70s. 

What were the basic results?

The studies examined different physical and psychological outcomes. The main effects were as follows.

Physical symptoms

• Walking – tai chi gave significant improvements on the six-minute walk test in people with heart failure and COPD. One study each for cancer and osteoarthritis found no effects on walking.
• Muscle strength – one COPD and one heart failure study found significant improvement in knee extensor strength, but there was no effect in the osteoarthritis studies.
• Getting up and moving – the osteoarthritis studies found tai chi improved the timed get up and go test result, as well as sit to stand times. One heart failure study found no effect.
• Chronic disease symptoms – tai chi significantly improved pain, stiffness and physical function in osteoarthritis. In COPD, there was a trend towards tai chi improving shortness of breath compared with control, but this was non-significant. No two cancer studies reported the same outcome. There was a trend for reduced fatigue in one study, but this had an extremely small sample size.
• Other physiological effects – heart failure studies found no effect on blood pressure or respiratory function.

Psychological outcomes

• Quality of life – tai chi had significant effects on osteoarthritis, but there were no significant effects in COPD, cancer or heart failure studies.
• Depression – tai chi was associated with significant improvements in depression symptoms in heart failure studies, but there were non-significant trends in osteoarthritis and COPD studies. In cancer, it was the control intervention (stress management) that improved symptoms rather than tai chi.  

How did the researchers interpret the results?

The researchers concluded that, "The results demonstrated a favourable effect or tendency of tai chi to improve physical performance, and showed that this type of exercise could be performed by individuals with different chronic conditions, including COPD, heart failure and osteoarthritis." 

Conclusion

This review searched the literature to summarise the effects of tai chi on four common chronic conditions. It identified a large number of trials collectively examining many different physical and psychological outcomes in a predominantly middle-aged to elderly population. 

The notable significant effects seemed to be for improvements in walking for those with heart failure, knee extensor strength for those with heart failure and COPD, and pain and stiffness for those with osteoarthritis. There were also trends for effects on depression and quality of life for people with heart failure and COPD.

The researchers concluded that tai chi could be performed by individuals for many different chronic conditions. However, this review can't demonstrate that tai chi will definitely have a positive effect if it's tried out by someone who has one of these chronic conditions.

Overall, the systematic review is a high-quality study design. However, the evidence is only as good as the studies included. The 24 individual studies in this review were widely different, and most results are based on one to a few studies.

Variations across the studies included:

• The type of tai chi, the overall duration of the intervention, and the frequency and duration of individual sessions.  
• The type of disease and severity, even within the same chronic disease category – for example, most cancer studies were in breast cancer, but even these varied in their stages, while another was just in "unknown cancer survivors".
• Osteoarthritis varied between spine, hip and knee, and the severity of pain and disability.
• The comparison groups varied – for example, some were just usual care or waiting list, others self-help education, some spiritual or psychological-related, and others varied physical activities such as walking, aerobics or stretching programmes. 
• As demonstrated by the results, the outcomes examined varied widely, and individual outcomes were only examined by one to four studies per condition.
• Sample sizes varied, and some were extremely small – for example, only 11 people in one study. Sometimes within these small studies, the dropout rate from the trial was also high – for instance, 10 people dropping out from a starting size of just 31 participants.

This makes it very difficult to say whether a certain type of tai chi will help individuals with chronic conditions.

Nevertheless, the benefits of exercising within our limits are well known – even when a person has a chronic disease. If you find tai chi enjoyable, this can only be a good thing.

The Tai Chi Union for Great Britain website has information about classes available in your area. 

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Decreasing portion sizes could cut obesity levels

Wednesday September 16 2015

One in four adults in the UK is obese

"Reducing the portion sizes … would help reverse the obesity epidemic, say researchers," BBC News reports. 

The researchers, who pooled the results of more than 70 previous studies, found a link between portion size and overeating.

Researchers found that increased portion size, packaging and the size of a plate led to people choosing larger amounts of food and eating more. It may be that the old saying "you have eyes bigger than your belly" rings true for some people. They eat what they are given, not what they need.

People also drank more when non-alcoholic drinks were provided in shorter, wider glasses and bottles than tall, thin ones. The researchers say that although the results were not surprising, they lend weight to the argument for portion sizes to be decreased to help reduce the UK's obesity epidemic.

It should be noted that the quality of the individual studies was rated as poor by the researchers, and most of the studies were conducted in the US, where portion sizes are infamously large.

The studies also did not look at whether people were able to reduce their intake over the long term through smaller portion sizes.

These limitations aside, it would seem a sensible option to choose a smaller portion if you are trying to achieve or maintain a healthy weight. Making sure you get your five portions of fruit and vegetables a day and increasing physical activity levels will also help.

Where did the story come from?

The study was carried out by researchers from the University of Cambridge, the University of Oxford, MRC Human Nutrition Research, the University of Plymouth and the University of Bristol. It was funded by the UK Department of Health Policy Research Programme.

The study was published in the peer-reviewed online medical resource The Cochrane Database of Systematic Reviews. As with all Cochrane studies, the research has been made available on an open-access basis, so it is free to read online.

The UK media reported the findings accurately and supported the notion that portion sizes have been increasing, which may be contributing to increasing obesity levels.

The Independent provided helpful expert commentary from one of the lead authors, Dr Gareth Hollands, that "helping people to avoid 'overserving' themselves or others with larger portions of food or drink by reducing their size, availability and appeal in shops, restaurants and in the home, is likely to be a good way of helping lots of people to reduce their risk of overeating". 

What kind of research was this?

This was a systematic review of studies that have looked at the effect of different portion sizes on the consumption of food, alcohol or tobacco. The researchers pooled the results together in a meta-analysis. 

Although this type of research brings together all of the evidence available for a topic, the results are reliant on the quality of the individual trials.

In this case, only randomised controlled trials were included, either comparing consumption between two groups or in individuals in crossover studies. However, despite this type of study design being the "gold standard", the researchers judged the studies to be at high or unclear risk of bias, so they say the overall evidence is of moderate to very low quality.

What did the research involve?

The study searched 12 medical databases and trial registries for relevant studies up to July 2013. Randomised controlled trials were included in the analysis if they compared the amount of food, alcohol or tobacco consumed or chosen, according to different portion:

• size
• shape
• package
• crockery dimensions

Standard Cochrane techniques were used for the search strategy in applying inclusion and exclusion criteria consistently across the identified search results, and when performing the statistical analyses.

What were the basic results?

There were 72 studies that met the inclusion criteria; 69 assessed food portion size and three looked at cigarette size. No studies were identified that assessed alcohol portion size.

Exposure to larger food portions, packaging or crockery size was associated with moderately increased food consumption for adults and children (standardised mean difference (SMD) 0.38, 95% confidence interval (CI) 0.29 to 0.46). 

The researchers estimated that if smaller portion sizes were used consistently across meals, the average daily calorie consumption could reduce by 144 to 228 calories per day. This would be equivalent to 4,032 to 6,384 less calories per month, which would equal a weight loss of one to two pounds (0.45kg to 0.9kg) if everything else stayed the same.

A meta-analyses of 13 studies found that increased portion or crockery size led to adults selecting a greater amount of food (SMD 0.55, 95% CI 0.35 to 0.75). This was not found in studies on children.

There was low-quality evidence from three studies that shorter, wider glasses or bottles compared to thin, tall glasses increased the amount of non-alcoholic drinks selection (SMD 1.47, 95% CI 0.52 to 2.43). 

Only one study looked at consumption of non-alcoholic drinks, which found that young adults drank more water if using shorter, wider bottles, but this was judged as very low-quality evidence (SMD 1.17, 95% CI 0.57 to 1.78).

Meta-analyses of the three studies on cigarette size found low-quality evidence that the length of cigarette did not influence the amount consumed. No studies were identified that looked at the effect of differently sized packs, such as packs of 10 cigarettes compared to packs of 20.

How did the researchers interpret the results?

The researchers concluded that, "people consistently consume more food and drink when offered larger-sized portions, packages or tableware than when offered smaller-sized versions". 

They say this "suggests that policies and practices that successfully reduce the size, availability and appeal of larger-sized portions, packages, individual units and tableware can contribute to meaningful reductions in the quantities of food (including non-alcoholic beverages) people select and consume in the immediate and short term". 

There was insufficient evidence for them to make recommendations for tobacco or alcohol portion sizes.

Conclusion

This systematic review and meta-analysis suggests that increased portion sizes, packaging and crockery influences the amount people choose to eat and actually consume. 

The methods used to produce this review are robust; however, all 72 identified studies were assessed as being at high risk of bias or of unclear risk. This reduces confidence in the results. Other limitations include:

• the majority of studies were conducted in the US, so the results may not be directly applicable to the UK, because of the potential differences in portion sizes
• most studies were not conducted on people who were trying to lose weight, so it is not clear how effective this strategy would be for weight loss
• the studies included only assessed food consumption or selection at one time point, or over short time periods. This means that the studies did not look at whether eating more at one meal was compensated for at subsequent meals that day
• the studies were performed in controlled environments such as a laboratory, so it remains unclear what effect portion size may have in "normal" environments over the long term

Overall, common sense tells us that people are likely to eat more if the portion size is bigger for a variety of potential reasons, such as:

• social norms – someone has decided the portion size is appropriate, which may challenge internal perceptions.
• there is a delay in the time it takes to feel full (satiety) than the time it takes to consume the food in front of you
• people may not want to waste food and are taught from an early age to "finish your plate"

Reducing portion size or the size of the plate the food is presented on is not a new concept for weight loss – it is a strategy employed by many diet regimes. Other strategies to help maintain a healthy diet can be found in the healthy eating pages. 

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UK ban on trans fats 'would save thousands of lives'

Wednesday September 16 2015

Trans fats can raise cholesterol levels

"Trans fat ban could save 7,200 lives by 2020, says study," The Guardian reports. This is the conclusion of a new modelling study looking at whether banning trans fatty acids – associated with "bad" cholesterol and heart disease – would improve public health outcomes.

Trans fats make up around 0.8% of the estimated energy consumption of the average UK diet. There are two types of trans fat: naturally occurring trans fatty acids found at low levels in meat and dairy products, and artificially made trans fatty acids labelled as hydrogenated fats or oils in some processed foods.

The artificial type became a popular ingredient for the food industry as they help prolong shelf-life while also improving taste. But research has shown a link between trans fats and heart disease. This led to several countries banning the use of artificial trans fats in food products.

In the UK there is no ban, but in 2012 most supermarkets and the bigger fast food chains agreed to sign up to a voluntary agreement not to use artificial trans fats. It is unclear how many products still contain trans fats.

The researchers calculated how many deaths they think could be avoided if a total ban was imposed, and what savings could be made in health and other costs.

While the figures are interesting, they are all based on assumptions fed into a mathematical model. It's hard to know how accurate these predictions are.  

Where did the story come from?

The study was carried out by researchers from the University of Lancaster, the University of Liverpool and the University of Oxford, and was funded by the National Institute for Health Research. 

It was published in the peer-reviewed BMJ and has been made available on an open access basis, which means anyone can read it free online. 

Most of the UK media covered the study accurately, although few questions were asked about how the figure of 7,200 prevented deaths had been reached.

Oddly, the Daily Mirror claimed a ban on trans fats "could prevent at least 10,000 deaths". They appear to have added a calculated 3,000 reduction in unequal deaths to the total 7,200 deaths prevented, when actually the 3,000 figure is part of the 7,200. 

What kind of research was this?

This was an epidemiological modelling study, which means it used data gathered about populations to create mathematical models to estimate the effect of possible changes in policy.

This type of study is a useful way to calculate the possible future effect of change, but it cannot be seen as a precise prediction of exactly what will happen. 

What did the research involve?

Researchers used several big data sets and the results of previous studies to construct mathematical models about the possible effects of three policies over the next five years:

• banning trans fats
• improving labelling of food containing trans fats
• banning trans fats only from restaurant and fast food outlets

They then calculated the effects in terms of deaths avoided or delayed, healthcare costs, costs to the economy, and the effect on health inequalities.

The researchers used the findings of a 2006 meta-analysis, which estimated the effect of how many trans fats we eat as a proportion of total energy intake. The meta-analysis found there are 23% more new cases of heart disease for every 2% of total energy that comes from trans fats.

The researchers then combined this figure with information from questionnaires from the National Diet and Nutrition Survey (an ongoing government project to monitor dietary trends) to find out what proportion of people's diets consisted of trans fats.

They also used data about the socioeconomic status of people in England, which assigned people into five groups depending on their wealth and levels of deprivation.

They used a mathematical model to calculate the different effect various policies might have on these groups – for example, people in the lowest socioeconomic group eat the most trans fats as percentage of diet, so any policy that affected this group more would have a bigger effect on health overall.

The researchers made assumptions for their models. For example, they assumed changing labelling would have a bigger effect on people in higher socioeconomic groups than on lower groups, and people from lower socioeconomic groups were more likely to eat at fast food outlets and less likely to eat at restaurants.

They did multiple calculations using this data to work out the possible reduction in deaths from heart disease, the savings to the taxpayer, the effect on health inequalities, and the savings to the economy overall. 

What were the basic results?

The researchers calculated an outright ban on the use of trans fats in food products would cut the amount of trans fats eaten by half, from 0.8% to 0.4% of total energy – the remainder would be the amount still consumed from naturally occurring trans fats in meat and dairy.

Their models found improved labelling or bans in restaurants and fast food outlets would, at best, achieve half that reduction, lowering trans fat consumption to around 0.6% of total energy.

They say most of the benefit from improved labelling or restaurant bans in terms of trans fat reduction would be seen among higher socioeconomic groups, so the policies would widen health inequalities.

In contrast, they say a total ban would affect lower socioeconomic groups more because they eat more trans fats, so it would narrow health inequalities. The researchers suggest the "gap" between the numbers of people from upper and lower groups who died of heart disease would narrow by about 3,000 people with a total ban.

They used the figures from the previous analysis to calculate the effect of this reduction in trans fat in the diet. They assumed deaths from heart disease would fall at the same rate as numbers of new cases of heart disease, giving a total figure of 7,200 deaths delayed or avoided over five years from a total ban (95% confidence interval [CI] 3,200 to 12,500).

They said improved labelling or restaurant bans might delay or avoid 1,800 to 3,500 deaths, depending on the model used. They claim a total ban would save £297 million (95% CI £131 to £466 million). These savings mainly represent savings in "informal care" – the care given to people with heart disease by friends and family.

They also included productivity at work and healthcare costs. Estimated direct healthcare savings are relatively small, at around £42 million, while estimated informal care savings are £196 million. 

How did the researchers interpret the results?

The researchers say their findings show that, "elimination of trans fatty acids from processed foods is an achievable target" and "would lead to health benefits at least twice as large as other policy options".

They warn trans fats "could creep back into processed foods" if action is not taken now to ban them completely. 

Conclusion

Trans fats are already at low levels in the UK diet compared with 10 or 20 years ago. However, this study suggests lowering them even further could reduce the number of people getting and dying from heart disease over the next five years.

This study does have limitations, however, which means we cannot rely on the findings to be precise. Any study that uses a mathematical model relies on the researchers making correct assumptions when they feed in the data.

The researchers say they have had to make assumptions based on little data in some cases. For example, there is no information about what proportion of the diet is made up of trans fats for those in the top socioeconomic class. We also don't know what proportion of trans fats are consumed in restaurants or fast food outlets.

More importantly, it is possible reducing consumption of trans fats will not have the effect on heart disease the researchers think it will. They used a study from 2006 that combined the results of previous trials to come up with their figure. But this study's finding that trans fats are linked to an increased chance of heart disease does not automatically mean reducing trans fats will reduce the chance of heart disease by the same amount.

However, it does seem likely reducing trans fats will reduce the numbers of people getting heart disease and dying from it. Whether or not banning trans fats will have exactly the effect the researchers predict is less certain. 

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Study finds North-South divide in UK life expectancy

Tuesday September 15 2015

Money may not buy you happiness, but it is linked to good health

"England's richest people 'live eight years longer than the country's poorest'," The Independent reports. 

A major new study has found a significant difference in life expectancy of the richer South East England compared to the poorer North.

The researchers found that overall life expectancy increased by more than five years from 1990 to 2013, from 75.9 to 81.3 years. The gap in mortality between men and women has also decreased, which is encouraging. 

However, more deprived areas have failed to catch up with less deprived areas, with a difference of more than eight years. Areas of deprivation were mainly located in the North, the Midlands and some areas of London.

There is also evidence that, while there has been an overall decline in mortality, there has been less of a reduction in the length of time people are living in poor health with chronic illness or disability. 

The study has shown where improvements have been made and areas that would benefit from more attention. Many of the leading causes of death are preventable through an active and healthy lifestyle and a good diet.

Where did the story come from?

The study was carried out by researchers from a number of institutions, including Public Health England and the London School of Hygiene and Tropical Medicine. 

Funding was primarily provided by the Bill & Melinda Gates Foundation. Additional funding for the study was provided by Public Health England.

The study was published in the peer-reviewed medical journal The Lancet on an open-access basis, so it is free to read online or download as a PDF.

The study has been widely reported in the UK media. Reporting of the study was accurate for all sources.

What kind of research was this?

This study used data from the Global Burden of Disease (GBD) 2013 study to analyse the burden of diseases and injuries in England, by region and within each region by level of deprivation. GBD is an ongoing global collaboration looking at trends in diseases that can cause death or disability.

Researchers compared this data with earlier years, going back to 1990. This method is able to look at large amounts of data for a long period to draw overall patterns and conclusions. However, it cannot provide definite answers as to why mortality or illness rates are as they currently stand, or why they have changed.

What did the research involve?

This study used data from the GBD 2013 study on causes of death, disease, and injury incidence and prevalence, as well as years lived with disability (YLDs) and disability-adjusted life-years (DALYs). DALYs is a term used by epidemiologists to measure the number of "healthy years" lost due to ill health, disability or early death.

Researchers looked at the following countries:

• England
• UK
• The first 15 EU members (excluding the UK)
• Australia
• Canada
• Norway
• US

The GBD 2013 study also provides independent and overlapping attributable risk for five tiers of risk factors:

1. All GBD risks combined.
2. Three large categories of metabolic, behavioural, and environmental and occupational risks.
3. Single risks, such as high blood pressure, and risk clusters, such as child and maternal under-nutrition or air pollution.
4. Single risks within such clusters, such as vitamin A deficiency or household air pollution.
5. Individual occupational exposure to cancer-causing substances or the division of childhood underweight into stunting, underweight and wasting.

The Index of Multiple Deprivation (IMD-2010) was used to measure deprivation. This is a government study that aimed to assess levels of deprivation in areas of the UK. 

Mortality data for the period 1990 to 2012 was obtained from the Office for National Statistics and split into regional and deprivations groups based on postcode.

What were the basic results?

The study found that from 1990 to 2013, life expectancy from birth in England increased by 5.4 years (95% confidence interval [CI] 5.0 to 5.8) from 75.9 years (95% CI 75.9 to 76.0) to 81.3 years (95% CI 80.9 to 81.7). A greater improvement in life expectancy gains was seen for men than for women.

Rates of age-standardised years of life lost (YLLs) reduced by 41.1%, which indicates a greater reduction in premature mortality compared with overall mortality. A small decrease was seen for age-standardised YLDs. DALYs were reduced by 23.8%.

The range in life expectancy across deprivation areas has stayed the same for men since 1990 – an 8.2 year difference between the least and most deprived areas. However, for women, the deprivation differences decreased from 7.2 years in 1990 to 6.9 years in 2013. In 2013, the leading cause of YLLs was heart disease, and the leading cause of DALYs was low back and neck pain. Leading behavioural risk factors were suboptimal diet and tobacco.

Overall, England ranked better than the other UK countries and was found to be the EU country with one of the largest gains in life expectancy among men (6.4 years). This is less than Luxembourg, but the same as Finland. 

All English regions except for South West England, gained at least six years, which is equal to or greater than all comparator countries except Austria, Finland, Ireland, Germany and Luxembourg. 

Among women, the increase in life expectancy in England overall was 4.4 years, which is equal to or in excess of all countries except Finland, Germany, Ireland, Luxembourg and Portugal.

How did the researchers interpret the results?

The researchers conclude that, "Health in England is improving, although substantial opportunities exist for further reductions in the burden of preventable disease. The gap in mortality rates between men and women has reduced, but marked health inequalities between the least deprived and most deprived areas remain". 

They go on to say that policies must address the causes of ill health and premature mortality. Action is needed to reduce risk exposures, support healthy behaviours, alleviate the severity of chronic disabling disorders, and mitigate the effects of socioeconomic deprivation.

Conclusion

This study used data to analyse the burden of disease and injury in England, and within each English region by level of deprivation. This was compared with the remaining constituent countries of the UK and with other comparable countries.

The researchers found an overall increase in life expectancy from 1990 to 2013. The decreased mortality gap between men and women is also encouraging. However, the inequality of life expectancy across regions of England has not improved. Those in more deprived areas have not yet reached the life expectancy of the less deprived in 1990.

Despite the overall decline in mortality, this has not been matched by a similar decline in the number of years people are living in poor health or with chronic illness.

The authors suggest the main reasons for improvement in life expectancy are reductions in: 

• cardiovascular disease
• cancer mortality
• chronic respiratory disease
• road injuries

However, they report that conditions still having a negative impact on life expectancy include:

• cirrhosis of the liver (related to alcoholic liver disease)
• mental disorders
• substance use

Strengths of this study are the large amount of population data used and the long follow-up period. Some limitations are that data was not available for some diseases or by specific deprivation level. The relative level of deprivation of an area may also have changed since the measurement tool was created, and the cross-country comparisons may not be as straightforward as presented.

The findings have indicated areas where improvement has been made and possible areas that would benefit from more attention.

Though not all diseases are preventable, poor health can be caused by risk factors such as poor diet, low levels of physical activity, smoking and alcohol consumption.

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Cannabis use may affect diabetes risk in the middle-aged

Monday September 14 2015

The effects of cannabis use on the metabolism are uncertain

"People who use marijuana may be more likely to develop pre-diabetes than those who have never smoked it," The Independent reports, after a US study found a link between long-term cannabis use and pre-diabetes.

Pre-diabetes is defined as having abnormally high blood sugar levels, but not high enough to meet criteria for diagnosis of type 2 diabetes.

The study enrolled around 3,000 healthy young US adults in the mid-1980s. Over the following years, researchers carried out regular medical assessments and questioned participants about their use of cannabis and other substances.

Cannabis use at the 25-year assessment, when the person was now in middle age, was associated with an increased risk of having pre-diabetes. However, there were no significant links between cannabis use and "full-blown" diabetes.

The main difficulty with this research is that the study design cannot prove direct cause and effect. Many other health and lifestyle factors could be linked to both cannabis use and diabetes risk, such as diet.

Cannabis is a notorious appetite stimulant – know as "the munchies", which often leads users to eat energy-rich, nutritiously poor snacks, such as crisps and sweets. If there is a link, it's possible that diet could be having an effect on diabetes risk, rather than cannabis itself.

While the short- and long-term effects of cannabis are not firmly established, the drug has been linked to mental health conditions such as psychosis and physical conditions such as lung cancer. 

Where did the story come from?

The study was carried out by researchers from the University of Minnesota and the University of California, San Francisco. It received various sources of financial support, including from the US National Institutes of Health.

The study was published in the peer-reviewed journal Diabetologia on an open-access basis, so it is free to read online as a PDF (384kb).

The Independent and the Mail Online's reporting of the study is accurate, although both articles could benefit from highlighting that this study cannot prove direct cause and effect. 

What kind of research was this?

This cohort study aimed to see whether cannabis use is associated with the presence or development of diabetes or pre-diabetes.

Pre-diabetes is when the person has blood glucose levels just below the threshold for meeting the criteria for diabetes. If the person doesn't make lifestyle changes, such as changing their diet, upping their physical activity and trying to lose weight, it can progress to type 2 diabetes.

Cannabis, or marijuana, has uncertain effects on a person's physical or mental health. In the US, where this study was based, it is the most frequently used illegal drug, with 18.9 million people over the age of 12 reportedly having used cannabis in 2012.

Recent studies have suggested that cannabis use may be associated with reduced odds of diabetes and other metabolic risk factors, such as a high body mass index (BMI) and waist circumference. The researchers report the possibility of bias with these studies, and the need for prospective studies to better examine these links.

In this study, researchers aimed to look at the link between self-reported cannabis use and the presence of diabetes or pre-diabetes (cross-sectional link) or the development of these conditions (prospective link).

The main limitation with this type of study is not being able to prove cannabis use has caused the diabetic conditions, as other factors may have had an influence – particularly with the cross-sectional association.   

What did the research involve?

This study involved participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. They were recruited from four urban areas in the US and aged 18 to 30 years at the time of enrolment in 1985-86.

At enrolment and each follow-up, the participants completed questionnaires and had clinical examinations, including blood tests and measurements of blood pressure and BMI. Questionnaires involved assessments of their health and lifestyle, including physical activity, alcohol, smoking and use of illegal substances.

The substance assessment asked specifically about the use of cannabis, crack or other cocaine, amphetamines or opiates in the person's lifetime or past 30 days, with frequency of once or twice, 3 to 9 times, 10 to 99 times, more than 100, or more than 500 times.

Pre-diabetes and diabetes were defined by blood glucose levels using American Diabetes Association criteria. For example, pre-diabetes was a fasting blood glucose of 5.6 to 6.9 millimole (mmol) per litre, and diabetes was a level of 7.0mmol per litre or greater.

The cross-sectional link between lifetime cannabis use and pre-diabetes or diabetes was assessed at the last follow-up assessment, around 25 years after enrolment.

The prospective link was examined between cannabis use seven years after enrolment and the later development of pre-diabetes or diabetes by year 25. The assessments included around 3,000 people.

When looking at the links between cannabis use and diabetes, the researchers took into account potential confounders – the use of other substances, smoking and alcohol, educational attainment, and examination findings, including BMI, blood pressure and cholesterol.  

What were the basic results?

Factors associated with cannabis use were being male, of white ethnicity, greater reported smoking, alcohol and other substance use, and greater physical activity.

Higher educational attainment and higher BMI were factors associated with less cannabis use. By the age of 24, 45% of the participants (1,193) had pre-diabetes and 357 had diabetes.

With full adjustment for all confounders, current use of cannabis was associated with about a two-thirds increased odds of pre-diabetes compared with never using the drug (hazard ratio [HR] 1.66, 95% confidence interval [CI] 1.15 to 2.38).

There were no significant links between pre-diabetes and former cannabis use. When broken down into frequency of use, there was a trend for increased lifetime use to be associated with an increased risk of pre-diabetes.

However, the only significant link was found for a lifetime use of 100 or more times being associated with a 40% increased risk of pre-diabetes (HR 1.40, 95% CI 1.13 to 1.72). There were no convincing links for a lower frequency use than this.

There was no statistically significant link between former, current or any lifetime use of cannabis and actual diabetes.  

How did the researchers interpret the results?

The researchers concluded that, "Marijuana [cannabis] use in young adulthood is associated with an increased risk of pre-diabetes by middle adulthood, but not with the development of diabetes by this age." 

Conclusion

This long-term study of healthy US adults found current cannabis use at the 25-year assessment – when the person had reached middle age – was associated with an increased likelihood of the person having pre-diabetes at this time.

Higher lifetime use of more than 100 times was also associated with an increased likelihood of pre-diabetes. However, there were no significant links between cannabis use and actual diabetes.

The main limitation of this study comes from the possibility of confounding. The researchers have attempted to take several confounders into account, including smoking and the use of alcohol and other substances.

However, various physical and mental health, lifestyle, personal and socioeconomic characteristics may be associated with both cannabis use and diabetes risk. For example, one possible factor that could be linked to both cannabis use and diabetes risk is poor diet.

Cannabis use can cause sudden and intense hunger pangs, nicknamed "the munchies". This can lead users to snack on foods with a high calorie and sugar content, but with little in the way of nutritional value. If maintained on a long-term basis, this type of diet can lead to obesity, which is a risk factor for type 2 diabetes.

This study is not able to account for the influence of all these factors, particularly as the main link was for the current use of cannabis at the 25-year assessment and pre-diabetes at the same time. This cannot prove that one thing has caused the other.

There was no link with type 2 diabetes itself. Pre-diabetes suggests the person may be on the border of developing diabetes, but they don't yet have the condition.

Another – admittedly unavoidable – limitation is that cannabis use was self-reported. This may be inaccurate, particularly when it comes to estimating the lifetime frequency of use. There is also the possibility when questioning people about their use of illegal substances that they may report never using them, when in fact they have.

This urban sample of US citizens may not be representative of everyone, particularly given they were enrolled 30 years ago. Patterns of cannabis use during the 80s and 90s may differ from use of the substance today. In particular, the strength of cannabis in terms of one of the active ingredients, tetrahydrocannabinol (THC), is thought to be much stronger than in the past.

The various possible effects of cannabis on physical and mental health – both in the immediate and longer term – are often debated. However, this study alone provides no proof that cannabis use will increase your risk of diabetes.

Cannabis remains a class B drug that is illegal to possess or distribute.  

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How hopping may help with osteoporosis risk in older people

Friday September 11 2015

Hopping may not be suitable for everyone

"Older people could reduce risk of osteoporosis by hopping for two minutes a day," the Daily Mirror reports. A UK study found regular hopping increased bone density in older men.

The study assigned more than 30 healthy older men to exercises on one leg and compared the change in bone density with the other leg.

It found five sets of 10 hops, with a 15-second rest between each set, every day increased the density of some parts of the hip. The men, aged 65 to 80 years old, were followed up with a second scan after 12 months.

Some of the media claim this has major implications for the prevention and management of osteoporosis. But these findings were from a group of healthy older males without osteoporosis and no other health conditions. It is unclear whether hopping would be effective, and safe, for people who actually have osteoporosis.

The follow-up time was also relatively modest – just 12 months – so it is uncertain whether this exercise regime would prevent bone fractures in the long term. Women feature in many of the newspaper pictures, but were not participants in this study.

Ways to prevent osteoporosis include weight-bearing exercises. For people aged over 60, this can include brisk walking. Read more about bone health. 

Where did the story come from?

The study was carried out by researchers from Loughborough University, the University of Cambridge, University Hospitals Leicester, and Derby Hospitals NHS foundation Trust.

It was funded by the National Osteoporosis Innovative Award, a Medical Research Council UK Interdisciplinary Bridging Award, and a Loughborough University Scholarship.

The study was published in the peer-reviewed Journal of Bone and Mineral Research.

This study has been widely reported in the UK media, with many sources suggesting hopping reduces the risk of a fracture. This was not reported in the paper and it is not yet known whether the bone density improvements demonstrated led to reduced numbers of fractures.  

What kind of research was this?

This randomised controlled trial aimed to evaluate the effects of these exercises on cortical and trabecular bone (found in the hip) and its 3D distribution across the hip.

This study design is the best way to assess such an effect, but as it was only the participants' legs that were randomised in this instance, both legs may have benefited from changes to other behaviours.  

What did the research involve?

Researchers recruited 50 healthy men of European origin who were aged 65 to 80. The men had no involvement in exercises of a strength, power or weightlifting nature for more than one hour a week, and had no health conditions likely to influence bone, neuromuscular function or their ability to perform exercises.

The "exercise leg" of each participant was randomly assigned (left or right) using sealed opaque envelopes. Limb dominance had no effect on allocation.

All participants were to perform hopping exercises on their exercise leg only and avoid any other changes to their physical activity or dietary habits during the trial.

The hopping exercise involved around 10 minutes of activity and consisted of five sets of 10 hops, with a 15-second rest between each set. This was performed in a variety of directions. Exercises were to be performed as high and fast as they could on a hard, even surface, while barefoot and when another person was nearby.

Measurements of bone mineral content were taken by CT scan before and after the study period. This was performed by a radiographer who was unaware (blinded) to leg allocation and efforts were made to standardise leg placement. Researchers were interested in how the exercise affects different parts of the hip.

Participants were to complete a seven-day food diary and health and physical activity questionnaire before the trial began. Anthropometric measurements (height, weight and BMI) and body composition were taken by DEXA (DXA) scan before and after the trial period. The men were followed up after 12 months. 

What were the basic results?

Of the 50 men who started the trial, only 34 remained for analysis. The withdrawal rate was 32% (16 men). This was mainly because of either health problems unrelated to the intervention, time commitments or discomfort during exercise.

The study found bone mineral density in the outer and spongy layers significantly increased over time in each leg. The density of the outer layer increased significantly more in the exercise leg, compared with the control leg.

There was a greater increase in density in the exercise leg than the control leg in terms of where the femur connects to the hip bone. Instability of the hip was reduced more in the exercise leg.  

How did the researchers interpret the results?

The researchers state short bursts of regular hopping exercises increased hip bone density, and exercise that targets localised regions of the proximal femur (the section of bone that connects the upper thigh bone to the hip) could produce greater increases in bone strength and resistance to fracture. 

Conclusion

This was a randomised controlled trial assessing the effect on hip bone density of hopping as a form of weight-bearing exercise in older men. The study found the hopping exercise to be of significant benefit to certain parts of the hip. But this study was performed in healthy men with no health concerns.

The study had a number of strengths and limitations. Strengths are that it was randomised in design, and the fact there was concealed allocation to the intervention group and blinded assessors, reducing the risk of bias. The researchers also performed calculations to estimate the number of participants needed for their study.

Limitations are that the study may have benefited from having a control group who did not take part in the hopping exercise, rather than just a randomly assigned leg. In addition, the sample size was quite small, the study did not assess physical activity or dietary habits after the intervention, and it was conducted in a group of healthy older men.

This means the findings may not be generalisable to other groups, especially those with osteoporosis, where boosting bone density would be of great benefit.

While this study has presented some significant findings, it is not possible to say whether this intervention would be of use to other older people who have health issues or are perhaps unsteady on their feet. The high drop-out rate of 32% suggests it may not be a suitable exercise for many men.

If you do have osteoporosis, hopping may not be the ideal exercise plan for you as there is a risk of falling, which could result in fracture. Your GP or the doctor in charge of your care should be able to recommend a suitable exercise plan.   

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No conclusive evidence that e-cigs tempt teens to smoke

Wednesday September 9 2015

A recent survey estimated that 1 in 5 UK teens had tried vaping

"Young people who try e-cigarettes are much more likely to start smoking, scientists have concluded," The Daily Telegraph reports. Though the conclusion, such as it is, is based on just 16 teenagers.

The study relies on results from two questionnaires, sent a year apart to about 700 young people in the US on whether they had ever smoked e-cigarettes or tobacco. 

Just 16 of these youngsters had tried e-cigarettes at the start of the study, six of them had tried a cigarette by the next year and five thought they might in the future.

Importantly, the research did not ask people how often they had used e-cigarettes or smoked tobacco, so we have no idea whether they were "addicted" to nicotine. 

This study leaves many unanswered questions, such as why young people tried e-cigarettes or tobacco.

Ultimately, this is a very small number to base such sweeping conclusions on. 

Where did the story come from?

The researchers are from the University of Pittsburgh School of Medicine, Dartmouth University and the University of Oregon in the US. 

The study was published in the peer-reviewed medical journal JAMA Pediatrics on an open-access basis, so it is free to read online.

It was funded by the National Cancer Institute and National Center for Advancing Translational Sciences.

The Telegraph and the Mail Online overplayed the fears about e-cigarettes being a gateway for teens into tobacco use. 

The Telegraph wrongly stated that 68% of those who had tried e-cigarettes went on to smoke tobacco – the true figure was 37.5%. The Mail Online reported the percentages correctly, but did not say that these results were based on just 16 young people who had tried e-cigarettes.

Also, the reporting of the study could give the impression that the findings represented a consensus opinion, which is certainly not the case. The study has come in for harsh criticism from independent experts in public health.

For example, Professor Robert West, professor of health psychology at UCL, is quoted as saying: "This kind of propaganda by major medical journals brings public health science into disrepute and is grist to the mill of apologists for the tobacco industry who accuse us of 'junk science'."

What kind of research was this?

This was a longitudinal cohort study, which means the researchers followed a group of people over time to see what happened to them. These studies are good at finding links between things, but cannot show that one thing causes another.

What did the research involve?

Researchers reviewed the results of questionnaires sent to people aged 16 to 26, which asked them about whether they had ever smoked tobacco cigarettes (defined as just one puff) or ever tried e-cigarettes, and about their attitudes to smoking. They followed up with another questionnaire one year later, and asked them the same questions.

They then used statistical analysis to see whether people who said they had tried e-cigarettes, but did not smoke and would not accept a cigarette if offered one, had tried smoking tobacco or changed their attitudes to it.

Of the people surveyed, 728 said they had never smoked and would not accept a cigarette if offered one. Only 507 of these people responded to the survey again a year later, so the researchers used statistical techniques to estimate the likely responses of some of the people who dropped out, based on responses from people in similar circumstances. This gave them a total of 694 people to base the survey on.

The researchers looked to see whether some other factors were also associated with the chances of someone trying a tobacco cigarette during the year. These included people's age, whether their parents smoked, whether their friends smoked, and how likely they were to try risky things.

What were the basic results?

Only 16 of the 694 people in the study had ever tried e-cigarettes at the start of the study. Of those, six (38%) tried a tobacco cigarette during the year of the study. Another five (31%) said they might try a tobacco cigarette if they were offered one, but had not done so yet.

Young people who had not tried an e-cigarette at the start of the study were less likely to say they had tried a tobacco cigarette at the end of it. The study found 65 of the 678 (10%) who had not tried an e-cigarette went on to try tobacco, and 63 (9%) said they might try a tobacco cigarette if offered one.

After adjusting their figures to take account of other factors, the researchers calculated that people were eight times as likely to try tobacco in the following year if they had tried an e-cigarette (adjusted odds ratio (AOR) 8.3, 95% confidence interval (CI) 1.2 to 58.6).

Looking at other factors that were linked to the chances of smoking tobacco, the study found young people who said they were open to trying risky things were more than twice as likely to try tobacco (AOR 2.6, 95% CI 1.3 to 5.2), and those who had more friends who smoked were almost twice as likely to try tobacco (AOR 1.8, 95% CI 1.2 to 2.9).

Not surprisingly, people who had tried e-cigarettes were more likely than those who had not tried them to say they were open to trying new or risky things.

How did the researchers interpret the results?

The researchers said their findings showed that e-cigarettes might make young people more likely to try smoking tobacco. They said: "Because e-cigarettes deliver nicotine more slowly than traditional cigarettes, they may serve as a 'nicotine starter' allowing a new user to advance to cigarette smoking," as they get used to the effects. 

They also say that using e-cigarettes might lead people to get used to the habit of smoking. They say the results of their study "support regulations to limit sales and decrease the appeal of e-cigarettes to adolescents and young adults".

Conclusion

On the face of it, this study seems to support the idea that young people progress to smoking tobacco via e-cigarettes. However, there are many limitations, which means we cannot draw such a conclusion from the study findings.

The first serious limitation is that only 16 of the 694 young people in the study had actually tried e-cigarettes. With numbers so small, we cannot be sure the results are reliable. There is a high chance that another group of 16 young people who had tried e-cigarettes might have given different answers.

Also, this type of study can never prove that one thing (in this case trying e-cigarettes) causes another (trying tobacco cigarettes). Young people try lots of things while they grow up, and some people are more likely than others to take risks. It is perhaps not surprising that those who try e-cigarettes are also more likely to try tobacco.

The language in the study could be misleading. For example, it describes people who had ever tried an e-cigarette as "e-cigarette users" and people who have taken even one puff of a cigarette as "smokers". Teenagers may try something once and then never try it again. 

It also talks about young people's "progression to smoking", which you might think means the numbers who had actually started to smoke. However, the definition of progression includes those who moved from saying they would definitely not accept a cigarette if offered one, to saying that they were not likely to accept one but could not rule it out completely. 

This may be why The Daily Telegraph got its figures wrong – it combined the young people who had tried smoking with the young people who had not ruled it out completely.

It is important to know whether e-cigarettes encourage people to start smoking tobacco. Tobacco is much more harmful than e-cigarettes, because of the toxins created when tobacco is burned. A recent evidence review carried out by Public Health England stated that e-cigarettes were probably 95% safer than smoking tobacco.

This study does not add much to our knowledge about whether e-cigarettes encourage young people to start smoking tobacco. We would need to see bigger, more detailed studies over time that look at how often people use e-cigarettes and tobacco, to get closer to answering that question.

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Does lack of sleep make you susceptible to common cold?

Tuesday September 1 2015

Having a cold can make you feel miserable

"Sleep longer to lower risk of catching cold," says The Daily Telegraph of research on how sleep duration and quality could affect your risk of catching a cold.

In this small, research experiment, electronic sleep sensors and records of how much volunteers slept were used to determine sleep patterns before the volunteers were given a dose of a common cold virus. Researchers then looked at whether they developed cold symptoms over the following days.

Those who slept less than five hours were four-and-a-half times more likely to catch a cold than those sleeping more than seven hours a night. A similar result was found for those sleeping five to six hours. Those who slept between six and seven hours were at no greater risk of catching a cold.

These findings support the importance of a good night's sleep in terms of health and wellbeing, but it doesn't prove sleep to be the single direct cause of a cold.

Many factors will inevitably determine whether you catch a cold – and although the researchers tried to account for some of these factors they could together be influencing people's susceptibility to the common cold.

Rather than worry about how long you've slept, simply try to keep your hands clean to reduce your chance of getting or spreading common cold viruses.

Where did the story come from?

The study was carried out by researchers from the University of California, Carnegie Mellon University and the University of Pittsburgh Medical Centre. Support for the study was provided by the National Center for Complementary and Alternative Medicine, the National Institute of Allergy and Infectious Diseases, National Institute of Health grants and the National Heart, Lung and Blood Institute.  

The study was published in the peer-reviewed journal Sleep.

This has been reported widely and, for the most part, accurately in the UK media. However, the Daily Telegraph's statement that "lack of sleep is the most important factor in determining whether someone will catch a cold" gives a misleading impression of the findings of this controlled experiment. It is likely that exposure to the cold viruses and lack of good hand hygiene are the most important factors in the spread of cold, but these were not examined in this study. Its headline assumption that you should "sleep longer to lower risk of catching cold" is also not necessarily supported by this evidence.

What kind of research was this?

This is a prospective study that looked at whether shorter sleep duration and interrupted sleep could predict susceptibility to the common cold. The study involved monitoring the sleeping habits of healthy, infection-free volunteers for a week before giving them nasal drops containing a common cold virus (rhinovirus 39). They were then monitored for the development of symptoms of the common cold.

This is a good way of observing how a particular exposure (in this case, sleep quality) may be associated with a subsequent outcome (in this case, the development of a common cold). However, it still can't prove direct cause and effect, as other factors could be involved.

What did the research involve?

Researchers recruited 164 healthy volunteers, comprising 94 men and 70 women aged 18 to 55 years old. Volunteers were excluded if they:

The volunteers were enrolled two months before being given the rhinovirus dose. During that time they completed questionnaires, two weeks of daily interviews to assess emotions, and underwent a week of sleep behaviour monitoring using a combination of wrist actigraphy (by a kind of wrist-worn electronic motion-sensing device called an actiwatch) and sleep diary. Blood samples were taken before and after this two-month period to assess antibody levels.

Sleep measurements were taken using the actiwatch for seven nights. This measured total sleep time, used to estimate sleep duration, and fragmentation index, which is a measure of restlessness during sleep. The volunteers also filled in sleep diaries, reporting the time they went to sleep, what time they woke up and how long it took to fall asleep.

Volunteers were then given a dose of rhinovirus via a nasal dropper. They were considered to have a cold if they were infected and met illness criteria. To be infected, their virus-specific antibodies must have increased at least fourfold. Illness criteria were either:

• a total adjusted mucus weight of 10 or more grams (assessed by collecting and weighing all their used tissues) 
• a total adjusted nasal clearance time of 35 minutes or longer (assessed by administering a coloured dye to the nasal passage)

The researchers looked for the association between sleep quality and the common cold, taking into account potential confounding factors, including:

• age
• sex
• race
• household income
• season in which trial occurred
• health habits – such as physical activity, smoking, alcohol consumption
• psychological variables – perceived socioeconomic status, perceived stress, positive emotional state

What were the basic results?

Sleep duration was categorised as:

• less than five hours
• five to six hours 
• six to seven hours
• more than seven hours

The study found that shorter sleep duration as recorded by the actiwatches was associated with increased risk of developing the common cold.

Participants who were recorded as having less than five hours' sleep had an increase of four-and-a-half times the risk compared with those sleeping more than seven hours a night (odds ratio [OR] 4.5, 95% confidence interval [CI] 1.08 to 18.69). A similar result was found for those sleeping five to six hours a night (OR 4.24, 95% CI 1.08 to 16.71). Those who slept between six and seven hours were at no greater risk (OR 1.66, 95% CI 0.40 to 6.95).

Sleep fragmentation and self-reported sleep durations were not found to be significant predictors of cold susceptibility. These findings remained after adjusting for all measured confounding factors.

How did the researchers interpret the results

The researchers conclude that: "Shorter sleep duration, measured behaviourally using actigraphy prior to viral exposure, was associated with increased susceptibility to the common cold."

Conclusion

This study assessed the effect of sleep duration and fragmentation on common cold susceptibility.

It demonstrated that those who had less than six hours' sleep a night were at increased risk of catching a cold after direct exposure using the nasal dropper, compared with those having more than seven hours a night.

This finding matches previous work suggesting that poor sleep can lead to adverse health outcomes. However, the study cannot prove poor sleep as the single direct cause of susceptibility to infection.

The researchers took care to control for various possible confounders but may not have been able to capture all of the factors that could influence sleep time and quality, and also separately influence susceptibility to infection. These could include, for example, long working hours, family commitments, and physical or mental health problems.

Few people were included in the study, and as a result, the confidence intervals around the risk estimates are wide (for example, 1.08 to 18.69). This suggests uncertainty around the exact size of the risk, so we cannot be sure the risk is as greatly increased as it appears.

Some outcomes were self-reported and this is prone to bias. However, these outcomes were also objectively assessed using actigraphy, and this adds strength to the study.

It's also worth noting that the study only recruited from one area and did not include children or older adults, so we do not know whether the results would be generalisable to other populations.

Overall, the results do support the importance of good sleep. However, this may be affected by many factors, such as stress levels, lifestyle and family life. There are a range of things you can do to help you get to sleep, such as:

• avoiding caffeine later in the day
• avoiding heavy meals late at night
• setting regular times to wake up
• using thick curtains or blinds, an eye mask and earplugs to stop you being woken up by light and noise 

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