Elderly living near noisy roads have 'increased stroke risk'

Wednesday June 24 2015

Is living in the ‘Big Smoke’ bad for your health?

“Living in a neighbourhood with noisy road traffic may…increase the risk of stroke,” The Guardian reports. Researchers looked at noise levels across London and found a link between high levels of noise and increased risk of hospital admission for stroke, with the risk slightly higher in older people.

This ecological study included the 8.6 million inhabitants of London and assessed day and night-time exposure to levels of road traffic noise in excess of 55 decibels (dB), which is roughly equivalent to the sort of background conversation you would hear in a restaurant.

55dB is the threshold set by the World Health Organization beyond which health problems are possible in relation to cardiovascular diseases, such as stroke and heart disease.

This study is now complete and has found some small associations, mainly in terms of increased stroke risk. The population level findings observed were small and could not account for all possible confounders. They may also not represent findings on an individual level. 

There are steps you can take to compensate for any small increased risk of stroke, such as eating a healthy diet, taking regular exercise, stopping smoking if you smoke and sticking to the recommended guidelines for alcohol consumption. 

Read more about stroke prevention.

Where did the story come from?

The study was carried out by researchers from the London School of Hygiene and Tropical Medicine, Imperial College London, Imperial College Healthcare Trust, and Kings College London. Funding was provided by the UK Natural Environment Research Council; Medical Research Council; Economic and Social Research Council; Department of Environment, Food and Rural Affairs; and the Department of Health.

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

Generally, the UK media reported the story accurately, with most sources making clear that a cause and effect relationship had not been proven, and that more research is needed.  

What kind of research was this?

This was an ecological study designed to assess whether higher noise levels are associated with greater risk of cardiovascular disease and death at a population level. This study design is suitable for assessing this kind of research question, but will not provide conclusive answers.

What did the research involve?

The study included the 8.61 million inhabitants of London (within the M25) from 2003 to 2010. It examined the effects of their exposure to road traffic noise, independent of air pollution, on all-cause cardiovascular death, as well as on cardiovascular hospital admissions in adult and elderly populations.

Associations of day (7:00 to 22:59) and night-time (23:00 to 06:59) road traffic noise with cardiovascular hospital admissions and all-cause and cardiovascular death in all adults (≥25 years) and elderly (≥75 years) were assessed through modelling. The researchers made adjustments for the possible confounding effects of:

• age
• sex
• area-level socioeconomic deprivation
• ethnicity
• smoking
• air pollution
• “neighbourhood spatial structure” – the actual physical environment of the region being studied

Traffic noise exposure was categorised in five-decibel increments:

• less than 55 (reference)
• 55 to 60
• more than 60

Hospital admission data was taken from Hospital Episode Statistics and are held by the UK Small Area Health Statistics Unit (SAHSU). Death and population data was supplied by the Office for National Statistics, derived from the national mortality registrations and the Census, and are held by SAHSU.

For assessing outcomes, the first registered emergency hospital episode of each year for all cardiovascular causes, coronary heart disease and stroke were used.

Deaths were classified according to the underlying cause on the death certificate; causes included in this analysis were from all natural causes, all cardiovascular causes, coronary heart disease and stroke.

Data was also collected of the person’s age, sex and postcode of residential address at the time of admission or death.

What were the basic results?

The total number of hospital admissions from cardiovascular causes was 400,494 among adults, and 179,163 among the elderly. There were 442,560 adult and 291,139 elderly deaths.

The average (median) daytime exposure to road traffic noise was 55.6dB.

Daytime road traffic noise increased the risk of hospital admission for stroke by 5% in adults, and 9% in the elderly in areas >60 compared with <55dB (baseline). Similar levels were observed when comparing 55 to 60dB to baseline; this was 4% in adults and 6% in the elderly. A small increased risk of hospital admissions for all cardiovascular diseases was seen in the elderly group exposed to daytime road traffic noise of 55 to 60dB when compared to the lower level group, but not for above 60dB.

Night-time road traffic noise of between 55 and 60dB was associated with a 5% increased risk of stroke among the elderly. Levels above this were not significant.

Daytime road traffic noise was associated with a 3-4% increased risk of death from any cause in adults and the elderly in areas exposed to more than 55dB.

How did the researchers interpret the results?

The researchers conclude: “Results suggested small increased population risks of all-cause mortality and cardiovascular mortality and morbidity, particularly of stroke in the elderly, at moderate levels of road noise exposure”.

Conclusion

This modelling study has examined the associations of exposure to traffic noise, independent of air pollution, on all-cause and cardiovascular mortality, as well as on cardiovascular hospital admissions in adult and elderly populations.

It has shown a link between increased noise from traffic pollution and risk of hospital admission for stroke and death. Possible reasons for deaths were most likely to be linked to heart or blood vessel disease, which could be due to increased blood pressure, sleep problems and stress from the noise.

The limitations of this study are that the exposure model used is likely to overestimate noise at low exposure levels and underestimate noise in areas with heavily trafficked minor roads. This may result in bias when analysing dose-response relationships.

The model did not take into account population activities, such as working and commuting outside residential areas, or residence characteristics, such as windows towards roads or building materials. The researchers did not have data on residential histories, which may have introduced further exposure misclassification.

Associations found in this study are in agreement with some, but not all, other previous work in this area, so caution should be taken with interpreting this small increased risk. There was often a lack of dose-response relationship, which requires further investigation. The whole populations study used London inhabitants as their population, which may reduce the generalisability of the findings to other populations and also on an individual level.

If this association was found to be true, changes would have to be made by legislation; however, to reduce your own risk of cardiovascular disease, it is important to make the right lifestyle choices which protect against both heart disease and stroke.

These include eating a healthy diet, taking regular exercise, stopping smoking if you smoke and sticking to the recommended guidelines for alcohol consumption.

Read more about cardiovascular disease prevention. 

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A case report about skinny jeans sparks media frenzy

Tuesday June 23 2015

If you are going to be active, comfortable clothes are the way to go

The UK media have had a field day with the suggestion that "Skinny Jeans Could Be Bad for Health".

They have taken the opportunity to indulge in some shameless clickbaiting by showing photos of various skinny-jean-wearing celebs such as Russell Brand, Kate Moss, Harry Styles and the Duchess of Cambridge.

By the tone of the reporting you could assume that hordes of hipsters are having skinny-jean-related health problems. In fact the furore has been sparked by just a single case report.

A woman in Australia who, after squatting for a long time while wearing skinny jeans, had severe ankle weakness. She fell over and could not get back up by herself, and ended up having her jeans cut off and staying in hospital for four days until she recovered.

It is thought that she developed a condition called compartment syndrome, where pressure in an enclosed bundle of muscles can adversely affect muscle and nerve function. This can sometimes occur, for example, as a result of a crush injury, or in people who are wearing a plastic cast, which constricts swelling tissue.

Given the fact that many people wear skinny jeans and this is the first report of this kind of severe problem, it is likely to be a rare occurrence. If you know you’re going to be squatting for long periods, even if it’s just for your comfort and the safety of your jeans, commonsense dictates that it’s probably better to wear looser trousers. Also make sure you take regular breaks to stretch your legs.

Where did the story come from?

The case study was written up by researchers at the Royal Adelaide Hospital in Australia. No specific funding was reported for the study and the researchers reported no conflicts of interest.

The case was published in the peer-reviewed Journal of Neurology, Neurosurgery and Psychiatry.

Many news sources covered this story. We suspect that this was because it gave them an excuse to carry photos of skinny-jean-wearing celebrities such as the Duchess of Cambridge. Call us cynical, but we doubt a case report involving anoraks or thermal underwear would generate the same level of coverage.

BBC News and The Guardian make it clear that the squatting was a major factor, and the jeans made the effect worse. The Daily Mail focuses on the jeans, suggesting that they "drastically reduced the blood supply to her leg muscles, causing swelling of the muscles and compression of the adjacent nerves". This is not quite true, as the blood supply to her feet was normal and doctors believed it was the prolonged squatting that started the problem, and her jeans made it worse. The Mail does not mention the squatting until later in the article.

What kind of research was this?

This was a case report describing a woman who presented with severe weakness in her ankles, what the doctors found and how she recovered.

Doctors will often publish reports of unusual cases they have seen, or phenomena that have not yet been described in medical literature. These reports can be useful for describing unusual conditions, or rare side effects of treatments or combinations of circumstances that have never been seen before. As they describe only one person, it can be difficult to be absolutely certain of what causes these events, and also to know how frequently they occur.

What did the research involve?

The researchers describe the woman’s symptoms and the results of their investigations.

What were the basic results?

The 35-year-old woman came to hospital after experiencing severe ankle weakness, which led to her falling over and not being able to get up by herself.

The doctors found out that the day before she had been helping a relative move house, and had been squatting for many hours cleaning cupboards. She was wearing skinny jeans while doing this, and felt that they were becoming tighter during the day. When she was walking home she realised her feet were feeling numb and she was not able to pick them up off the floor properly. This resulted in her tripping and falling. She then spent several hours on the floor until she was found.

When the doctors examined her, her lower legs were swollen and her jeans had to be cut off. Her ankles showed weakness and she had poor toe movement, she also had reduced feeling in her feet and the sides of her lower legs. Her hips and knees showed normal muscle strength.

One of the nerves travelling down her legs was found to not be transmitting electrical signals to her feet properly. Testing also showed that there had been some muscle damage, a part of something called "compartment syndrome", which occurs when too much pressure builds up in the muscle. There were also problems with the nerves lower down in her leg.

The woman was given intravenous fluids and her legs gradually improved. After four days she was discharged from hospital and could walk unaided.

How did the researchers interpret the results?

The researchers say that the sort of nerve problem the woman had has been known to be caused by the nerve being squashed at around the knee, for example through prolonged squatting. They suggest that the woman’s squatting probably started the problem off, and caused her calves to start to swell. This swelling caused problems with other nerves in the calf, and the skinny jeans were "likely" to have made this worse by causing even more pressure as her legs swelled. They say that while there have been reports of compression of nerves in the thigh with skinny jeans, this case of nerve problems in the lower leg is a "new neurological complication of wearing tight jeans".

Conclusion

This study describes a case where the combination of squatting for a prolonged period while wearing skinny jeans seems to have led to severe ankle weakness.

With this kind of one-off event, it is difficult to be absolutely certain what causes it, but doctors look at the circumstances around the event and see what might explain it. They concluded that it was the extensive squatting that probably started the problem off, but once the woman's legs started to swell the jeans probably made it worse.

Given the fact that many people wear skinny jeans and this is the first report of this kind of severe problem, it is likely to be a rare occurrence. If you know you’re going to be squatting for long periods it is important to take breaks and stretch your legs, and even if it’s just for comfort and the safety of your jeans, it’s probably better to wear looser trousers. You don’t want to end up as a "fashion victim". 

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Being a 'couch potato' linked to increased anxiety risk

Monday June 22 2015

Prolonged sitting is thought to slow the metabolism

“Being a couch potato is bad for your mental health,” the Mail Online reports. However, the evidence gathered by a new review is not as clear-cut as the headline would lead you to believe.

The review summarised the results of nine studies on the link between anxiety symptoms and sedentary behaviour, such as using a computer or watching TV. 

Overall, five of the nine studies found a positive link – that as time spent sitting went up, so did the risk of anxiety symptoms.

However, the results of a review are only as reliable as the studies it includes, and in this case they weren’t very good. The majority of studies looked at sitting and anxiety at one time.

This can’t prove cause and effect, as we are faced with the classic “chicken and egg” dilemma: does sedentary behaviour cause anxiety symptoms, or are anxious people likely to spend more time sitting?

Importantly, we don’t know whether the studies took account of other factors that could be influencing the results, and most looked only at anxiety symptoms, not a diagnosis of anxiety.

Overall, this review doesn’t provide conclusive proof of a definitive link. The occasional boxset binge is probably not going to trigger general anxiety disorder by itself, but it is important to balance this out with regular exercise. Aside from the physical health benefits of exercise, it can also often reduce feelings of depression and anxiety.

Where did the story come from?

The study was carried out by researchers from the School of Exercise and Nutrition Sciences at Deakin University in Burwood, Australia. No sources of funding are reported and the authors declare no conflicts of interest.

The study was published in the peer-reviewed medical journal BioMed Central Public Health. BioMed Central (BMC) publishes all its articles on an open-access basis. This means you can read the original research for free online, or download the PDF.

In concluding that being a couch potato is bad for your mental health and can cause anxiety, the Mail does not consider the important limitations of the studies on which this review is based. This includes that they cannot prove causation, and the majority have not looked at diagnoses of mental health illnesses.

What kind of research was this?

This was a systematic review aiming to look at the links between sedentary behaviour and anxiety levels.

Sedentary behaviour encompasses activities that require limited or no body movement, such as sitting (e.g. for work, travel), and screen-based activities, such as computer use, computer gaming and watching TV.

The researchers discuss how time spent sedentary has been associated with worse health in adults, irrespective of whether people do the recommended level of physical activity. Research has linked it to various chronic diseases, such as cardiovascular disease, diabetes and cancer. Studies have also looked into links with depression, but have not looked into other mental health illnesses, such as anxiety. Therefore, the research team decided to explore the potential effect of sedentary behaviour on anxiety.

A systematic review is one of the best ways of identifying and summarising all the available research on a particular issue. However, the review findings are only as good as the quality of the evidence they include. If the evidence is shaky, the review findings may be similarly unreliable.

What did the research involve?

The researchers searched literature databases for studies published from 1990 to end-2014. They looked for studies reporting keywords such as mental health or anxiety linked to sedentary behaviour, or computer or TV viewing. Eligible studies could be observational, including cross-sectional studies or prospective cohorts, or experimental study designs. The study populations could be children or adult, provided they only had anxiety or anxiety symptoms and did not have chronic medical conditions that could be affecting mental health.

The researchers assessed quality of the included studies and extracted the relevant data.

A total of nine relevant studies were eligible for inclusion in the review, seven of which were cross-sectional studies and two had a prospective (follow-up) design.

The studies varied in their included populations, measures and assessments. Seven studies included adults and two included children. Study sample sizes ranged from 189 to 13,470. Two of the studies came from Australia, two from the Netherlands, and the remaining came individually from the UK, US, Spain, China and Singapore.

Seven of the studies assessed sedentary behaviour by self-reporting questionnaires, asking people questions such as how much time they spent sitting, watching TV or viewing a computer screen. One of the studies in children had used parent reporting of the time the child spent in front of a screen. Four of the studies had looked specifically at leisure viewing, one looked at occupational viewing, and the others measured total daily time spent sedentary.

Only one of the studies used an accelerometer to objectively measure sedentary time and activity. When looking at anxiety, only one of the studies actually used a diagnostic interview to look for the presence of an anxiety disorder; the others all looked at symptoms. One of the studies used parent reporting of their child’s emotional symptoms on the Strengths and Difficulties Question; the other studies all assessed self-reported anxiety symptoms on a range of questionnaires.

What were the basic results?

Of the nine included studies, five – four cross-sectional and one prospective – found a positive link between sedentary behaviour and risk of anxiety. The other prospective study found no link, and the remaining three cross-sectional studies found either no link or the opposite link.

The researchers considered that, overall, there was moderate evidence for a link between sedentary behaviour and anxiety risk. Moderate evidence was defined as consistent results in one high-quality study and at least one weak-quality study; or consistent results in two or more weak-quality studies.

Looking more specifically into the results, four of five studies examining sitting times had found positive links. Two of four studies had found positive links with screen time (TV, gaming or computer). Two of three studies had found positive links with TV viewing, and one of two with computer use.

How did the researchers interpret the results?

The researchers conclude: “Limited evidence is available on the association between sedentary behaviour and risk of anxiety. However, our findings suggest a positive association (i.e. anxiety risk increases as sedentary behaviour time increases) may exist (particularly between sitting time and risk of anxiety). Further high-quality longitudinal/interventional research is needed to confirm findings and determine the direction of these relationships.”

Conclusion

This systematic review suggests that the more time people are sedentary (not moving much), the higher the risk of anxiety symptoms.

It has strengths in its systematic review methods, searching the literature for studies published over 25 years that examined the association, and assessing the quality of these studies. However, the results are only as reliable as the studies it includes. There are also important limitations to consider:

• The majority of studies in this review – seven of nine – were cross sectional. This means they questioned sedentary time and anxiety symptoms at once. These studies can show associations, but they cannot prove cause and effect. It is possible that sedentary time caused the anxiety symptoms, but just as possible that anxiety symptoms could have led to more sedentary behaviour.
• The possibility of confounding is another important limitation – both in the cross-sectional studies and the cohorts. From the information in the review, we have no idea whether the studies have taken into account the range of other factors that could be influencing any links between sedentary behaviour and anxiety symptoms. This could include physical and mental health illnesses, lifestyle (including diet and physical activity), environment and life events.
• The studies varied in their study methods, but most of them relied on self-reporting questionnaires, both for sedentary time and for the assessment of anxiety symptoms. For assessments of sedentary time, this could be inaccurate. For anxiety symptoms, this means the person doesn’t necessarily have anxiety. It is important to note that only one of the nine studies actually diagnosed anxiety; the other studies were looking at symptoms of anxiety. Without being an actual diagnosis of anxiety, is not known how many symptoms there were, or whether it would have actually be having an influence on the person’s daily life and wellbeing.
• The variations across the nine studies, including differences in age, nationality and type of sedentary time examined, mean the review conclusions aren’t particularly reliable. As the researchers say, further high-quality evidence is needed to confirm the links.

Despite the limitations, it is known that taking regular exercise has many health benefits, so reducing the time you spend sitting at work, while travelling or at home is a good thing.

Read more about why sitting too much is bad for your health. 

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New chlamydia vaccine shows promise after being tested on mice

Friday June 19 2015

Estimates say that over 100 million people have a chlamydia infection

“Researchers in the United States say they have developed a vaccine that can protect against chlamydia,” The Independent reports. Initial results in mice have shown promise in protecting against this common sexually transmitted infection (STI).

Chlamydia is one of the most common STIs in the UK, and can lead to female infertility. It can also cause blindness in babies if their mother has a chlamydia infection and babies are exposed to the bacteria when they are born.

Researchers tested a new vaccine that contains ultraviolet (UV) light, which killed chlamydia bacteria when attached to tiny man-made nanoparticles – these contained chemicals that tried to enhance the immune response. When given as a spray into the nose, or directly onto the internal surface of the womb, the vaccine protected the mice against chlamydia infection. If the mice were just given UV light that killed chlamydia bacteria without attachment to the nanoparticles, this actually made them more susceptible to infection.

This is early stage research, and more animal testing is needed before the vaccine could be tested on humans. Until human studies are carried out, we won’t know whether the vaccine is safe or effective.

Currently, the most effective way to prevent catching chlamydia is considerably more low-tech than nanoparticles; always use a condom during sex, including oral and anal sex.

Where did the story come from?

The study was carried out by researchers from Harvard Medical School and other research centres in the US and Saudi Arabia, and from the pharmaceutical company Sanofi Pasteur. It was funded by the National Institutes of Health, Sanofi Pasteur, the Ragon Institute, the David Koch Prostate Cancer Foundation, and Harvard University. Some of the researchers are inventors on patent applications relating to the vaccine technology tested in the study. Some had financial interests in biotechnology companies developing this type of technology.

The study was published in the peer-reviewed medical journal Science.

The Independent covered this study well. The headline does not over-state the impact of the research; the article says the research was carried out on mice, and also includes an expert comment highlighting the early stage of the research.

The Mail Online’s subheads suggest that the vaccine is a “jab” but the vaccine actually didn't work if injected; it only worked if given via the mucous membranes, such as into the nose or womb. The Mail's headline also suggests that chlamydia is the most common cause of infertility, but this may not be correct. There are many potential causes of infertility, and in about a quarter of cases no cause can be found.

What kind of research was this?

This was animal research that aimed to test a new vaccine against chlamydia.

Chlamydia is an STI caused by the bacteria Chlamydia trachomatis. Chlamydia is one of the most common STIs in the UK, and about two-thirds of those infected are aged under 25.

In around 70-80% of women, and half of all men, chlamydia does not cause noticeable symptoms. This has resulted in widespread infection, as people do not realise they are infected, so do not seek treatment.

While symptoms of chlamydia tend to be mild (if annoying), such as pain when urinating, complications of chlamydia can be very serious, such as infertility in women.

In the developing world, it is also a common cause of blindness in babies born to women with an active infection.

There is currently no vaccine against the disease. A chlamydia vaccine was last tested in the 1960s, and although it seemed to offer some protection initially, some people who had the vaccine had more symptoms when they were exposed to chlamydia than those who were given placebo (dummy treatment). Because of this, development of the vaccine stopped.

The chlamydia bacteria infect the mucus-producing (mucosal) surfaces of the body, such as the linings of the reproductive tract. Injecting vaccines against this type of infection often does not offer much protection, because the immune response does not easily reach the mucosal surfaces. Delivering vaccines directly onto the mucosal surface has not always worked well in the past for a variety of reasons, such as not producing a strong immune response or causing side effects. The current study wanted to test a new vaccine made by attaching killed chlamydia bacteria to tiny particles called nanoparticles, given directly onto the mucosal surfaces.

This type of animal research is essential for the early testing of vaccines and drugs, to test their effects and make sure they are safe for testing on humans. While they can give an early indication of whether a vaccine may work in humans, there's no certainty until they reach human trials.

What did the research involve?

The researchers developed a new vaccine by attaching UV light-killed chlamydia bacteria to tiny man-made nanoparticles. These nanoparticles acted as biodegradable “carriers” for the vaccine and also contained chemicals that enhance immune responses, called “adjuvants”.

They compared the effect of this vaccine in mice to an infection using live chlamydia or the UV light-killed chlamydia bacteria alone. They looked at what immune response these different approaches produced, and what happened when they exposed the mice to live chlamydia bacteria four weeks later. They also compared the effects of giving the vaccine through different routes – under the skin, directly onto the mucosal surface lining the womb (uterus) or the mucosal surface lining the inside of the nose.

What were the basic results?

The researchers found that vaccinating the mice with UV light-killed chlamydia bacteria into the uterus produced a different kind of immune response to infecting them with live chlamydia. When the mice were exposed to live chlamydia bacteria four weeks later, the ones which had been vaccinated with UV light-killed chlamydia bacteria actually had worse infections (more chlamydia bacteria) than those which had been previously exposed to the live chlamydia.

However, when the researchers vaccinated the mice with UV light-killed chlamydia bacteria attached to the nanoparticles, this prompted a different immune response to UV light-killed chlamydia bacteria alone. Giving this nanoparticle vaccination through the mucosal membranes of the nose or the uterus protected the mice when they were exposed to live chlamydia bacteria four weeks later. However, giving the nanoparticle vaccination by injecting it under the skin did not work.

The researchers identified that the reason mice experienced protection when the vaccine was given onto mucous membranes was the interaction between two different types of immune system cells called memory T cells. One set of these cells remained in the mucosal tissue of the uterus, and prompted a response from the other type when exposed to chlamydia infection.

How did the researchers interpret the results?

The researchers concluded that combining UV light-killed chlamydia bacteria with nanoparticle carriers changed the immune response compared to the UV light-killed bacteria alone, and “achieved long-lived protection” against chlamydia infection.

They suggest that their nanoparticle system is an efficient way of getting vaccines onto mucosal surfaces, and might also be useful for developing vaccines against other harmful infections that target these surfaces.

Conclusion

This animal research has tested out a potential new vaccine against chlamydia, which utilises UV light-killed chlamydia bacteria linked to tiny nanoparticles. The vaccine did protect against chlamydia infection in mice, if it was given directly onto the mucous-producing surfaces of the nose or uterus.

Previous attempts to make a chlamydia vaccine have not been successful, and the current research also identified that this may have been due to the type of immune response produced. This new approach prompts a different immune response, including “memory” cells, which remain in the mucosal tissue. These cells prompt an immune response if they are exposed to chlamydia infection again, allowing the mice to fight the infection off more successfully.

This type of animal research is essential for the early testing of vaccines and drugs, to make sure they are safe enough for testing on humans. Humans and animals are similar enough for these studies to give an early indication of whether a vaccine may work on humans. However, it will not be possible to say for certain whether this new vaccine is effective and safe until it does reach human trials.

Chlamydia is one of the most common STIs in the UK. Although there is no vaccine currently, you can protect yourself by:

• using a condom every time you have vaginal or anal sex
• using a condom to cover the penis during oral sex
• using a dam (a piece of thin, soft plastic or latex) to cover the female genitals during oral sex or when rubbing female genitals together
• not sharing sex toys

Read more about chlamydia prevention and sexual health in general. 

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Smoking causes half of all deaths in 12 different cancers

Thursday June 18 2015

Globally, tobacco kills six million people per year

“Roughly half of deaths from 12 smoking-related cancers may be linked directly to cigarette use, a U.S. study estimates,” the Mail Online reports. Due to similar smoking rates in the UK (19% of adults) and USA (17% of adults) there may be a similar pattern.

Researchers used data from previous studies to estimate the proportion of deaths from 12 cancers associated with smoking.

The researchers estimated that smoking may account for half of these cancer deaths overall.

Unsurprisingly, lung cancer was most strongly associated with smoking (accounting for 80% of deaths), followed by cancers of the mouth and throat.

It is important to note, however, that these are just estimates based on data taken from previous studies, which may have various limitations. Therefore, we cannot be certain that these figures on the proportion of cancers caused by smoking are 100% accurate – or directly applicable to the UK.

The results still make for sobering reading, with the World Health Organization (WHO) estimating that smoking kills nearly six million people a year worldwide, due to cancer and other diseases, such as heart disease.

If you are a smoker, the best thing you can do for your health is to stop smoking.

Where did the story come from?

This study was authored by researchers from the American Cancer Society in Atlanta; Harvard Medical School in Boston; National Cancer Institute in Bethesda, Maryland; and Fred Hutchison Cancer Research Center in Seattle. The analysis part of this work was funded by the American Cancer Society. Individual studies from which data was taken received various sources of financial support.

The study was published in the peer-reviewed medical journal JAMA Internal Medicine.

The Mail Online’s reporting of the study was accurate. However, one of the background quotes from the lead author – “e-cigarettes are now the most common form of tobacco use among high school students” – is open to criticism, as e-cigarettes do not contain any tobacco.

What kind of research was this?

This study was titled as a research letter, and the researchers used data from previous studies to estimate the proportion of deaths from 12 different cancers in the US in 2011 that could be attributed to smoking. 

The researchers say that the 2014 US Surgeon General’s Report estimated the number of cancer deaths overall and lung cancer deaths specifically that were caused by smoking. However, they missed out the other 11 that are reported to be caused by smoking. Previous data on smoking deaths due to these cancers is said to come from 10 or more years ago. Since then, smoking prevalence has decreased, but risk of cancer among smokers can increase over time. Because of this, the study aimed to look at more up-to-date information on specific cancer deaths in 2011.

The research used data from various previous studies and surveys. Specific methods on how these studies were identified and selected is not reported in this brief publication; therefore, it is not possible to comment on whether all relevant evidence will have been considered.

A systematic review would probably have provided more detailed information. However, these types of reviews can be both expensive and time-consuming, and some research teams just don’t have the resources to carry them out.

What did the research involve?

The researchers obtained information on smoking prevalence from the 2011 National Health Interview Survey. This was based on interviews from a nationally representative sample.

Age- and sex-specific cancer risk for former and current smokers came from cohort studies that had assessed smoking in questionnaires, and then followed the people up looking for risk of cancer and cancer deaths. One data source was the Cancer Prevention Study II, which included people aged 35 to 54 years (covering the follow-up period 1982-88), and the source for other age groups was the Pooled Contemporary Cohort (follow-up period 2000-11) which has pooled data from five cohorts.

Using information from these data sources, the researchers calculated the population attributable fraction (PAF) of smoking for different cancer deaths. The PAF is the proportion of the number of deaths that are caused by smoking, or by what proportion the number of deaths would be reduced if there was no smoking. 

What were the basic results?

In 2011, there were 345,962 cancer deaths in adults aged 35 or over with the 12 different cancer sites examined. The researchers estimated that 167,805, or 48.5% (95% confidence interval (CI) 46.2 to 51.2%), of these overall cancer deaths were caused by cigarette smoking. Smoking accounted for 51.5% of cancer deaths in men and 44.5% of cancer deaths in women.

By far the largest proportions of smoking-attributable deaths were cancers of the lungs and airways. 80% of these cancer deaths – broken down as 83% for men and 76% for women – were estimated to be caused by smoking. The second highest proportion was for cancers of the larynx (vocal cords), where smoking accounted for 77% (72% in men and 93% in women).

Smoking accounted for around half of all deaths of the mouth, throat and oesophagus (food pipe), and just under half of bladder cancers.

Smoking was attributable to around a quarter of cervical and liver cancers.

The remaining cancers examined where the PAF of smoking was less than 20% were those of the kidney, pancreas, stomach, bowel, and a type of leukaemia.

How did the researchers interpret the results?

The researchers conclude, “Cigarette smoking continues to cause numerous deaths from multiple cancers, despite half a century of decreasing prevalence. The smoking downturn is likely reflected in the generally lower proportions of deaths caused by smoking in 2011 than in 2000 to 2004”.

Conclusion

This study has used data from previously published cohort studies and national surveys to estimate the proportion of cancer deaths that can be attributed to smoking in men and women. They examined 12 cancers that are already known to be associated with smoking and estimated that smoking may account for half of them overall. The vast majority of cancers of the lungs and airways were estimated to be caused by smoking.

It is important to note that these are only estimates. The study has used data from cohort studies to inform the risk of different cancers in former and current smokers, and those who have never smoked. However, these cohort studies may have various inherent limitations and potential biases in their designs, which cannot be analysed here. For example:

• the populations studied may not be representative of everyone
• the follow-up period may be too short to capture all newly developed cancers and cancer deaths caused by smoking
• they may not have taken into account other confounders (e.g. alcohol intake, diet and physical activity)
• there may be inaccuracies around assessments of lifetime smoking habits
• they may not have been able to assess the effects of passive smoking from environmental exposure

Specific methods on how the cohorts and national survey were identified and selected are not reported in this brief publication. It is likely that the researchers will have selected the best available and most nationally representative evidence on which to form estimates. However, this cannot be assumed, and it is not possible to comment on whether all relevant evidence will have been considered.

Another point to bear in mind is that the cancers studied were selected as they are known to be linked to be smoking. It is possible that other cancers may be associated with smoking that are currently less well recognised. It is worth again highlighting that these are estimates for the US population – not the UK.

Despite limitations in terms of whether this study provides accurate estimates on the proportion of these cancer deaths that are caused by smoking, it nevertheless reinforces the health message. Smoking is known to have many detrimental effects on health, not only on risk of cancer, but for many other chronic diseases.

As the researchers conclude, “more comprehensive tobacco control, including targeted cessation support” seem to be an important way forward.

Even if you have been a smoker for many years, quitting will still provide a tremendous health benefit. For example, 10 years after you've stopped smoking, your lung cancer risk is half that of someone who has continued to smoke.

Read more methods you can use to quit smoking. 

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Does owning a cat put your family at risk of schizophrenia?

Monday June 15 2015

Cats don't usually show any symptoms of toxoplasmosis

“Scientists have discovered a link between people who own cats and the development of mental illnesses, including schizophrenia, and believe a parasite may be to blame,” The Independent reports.

The researchers suggest that toxoplasma gondii (T. gondii), a type of parasite found on infected cats, may be a cause of developing mental illness in later life. T. gondii was blamed for children’s poor reading skills in a study we analysed earlier this month.

The parasite has also been linked to an increased risk of suicide, as we discussed back in 2012.

This latest study used data from over 2,000 families in the United States to look at the number of people who were living with schizophrenia or schizoaffective disorder and owned a cat in childhood. This data was compared to findings of previous studies, conducted by the same study group, with the aim of confirming a link.

A large proportion of study participants were in contact with a household cat as a child, similar to the results found previously.

This study was unable to prove the link between cats and mental illness, and does not give any definite reasons for their observed links. Therefore, we should not be too concerned about the findings.  

Where did the story come from?

The study was carried out by researchers from the Stanley Medical Research Institute and Johns Hopkins University, in the United States. Funding was provided by the Stanley Medical Research Institute. No conflicts of interest were declared by the authors. The study was published in the peer-reviewed medical journal Schizophrenia Research.

This story has been reported by a number of UK media sources; however, describing cat ownership as having a “strong link” to schizophrenia is misleading. In fact, there are reports that owning a pet can be of value for some people, in terms of mental health and quality of life, such as older people and patients recovering from major illness.

What kind of research was this?

This study used data from a cross-sectional study conducted at the National Alliance for the Mentally Ill (NAMI) annual convention in 1982. Analysis of the responses was carried out to assess whether there was a link between cat ownership and schizophrenia. This type of study is unable to prove cause and effect, but it can show possible associations, which can provide a route for further research.

What did the research involve?

The researchers used data from a questionnaire conducted at the NAMI in 1982; participants had a family member with schizophrenia or schizoaffective disorder.

The study included 2,125 questionnaires of families who lived in 46 states and the District of Columbia, and attempted to replicate the findings of their previous research linking cat ownership and mental illness. As no control group was used in the 1982 questionnaire, the researchers used the “middle parents” group from the American Veterinary Medical Association (AMVA), as this population was the most similar to their study group.

Questions included details of pregnancy, childhood and family medical history, and cat and dog ownership up to age 17, including ages of pet exposure.

What were the basic results?

The number who owned a cat when the affected person was between birth and age 13 was 50.6%. This result is similar to those found in previous studies in 1992 (50.9%) and 1997 (51.9%). 

Among the “middle parents” control group from the 1992 AMVA, 42.6% owned a cat, which was virtually identical to the controls in the 1997 survey. The difference between the rate of cat ownership in the NAMI families and those in the AVMA control group was significant.

How did the researchers interpret the results?

The researchers suggest that cat ownership in childhood is significantly more common in families where the child later develops a chronic mental condition such as schizophrenia. They suggest this link may be due to the parasite T. gondii found on cats. They go on to say, “It is important to ascertain whether or not cat ownership in childhood is a risk factor for later schizophrenia, since it is a risk factor which could be minimised. We therefore urge our colleagues in other countries to collect data on cat and other pet ownership, and a major goal of this paper is to encourage such research”.

Conclusion

This study aimed to replicate the researchers' previous findings, which suggest that cat ownership in childhood is a possible risk factor for developing schizophrenia in later life. This study is able to draw a link, but cannot prove cause and effect. There is a suggestion that this link may be due to the parasite T. gondii, which is transferred from cats to humans if they come into contact with the faeces of infected cats, or eating or drinking contaminated food or water.

Even if this link between cats and mental illness was proven to be true, contact is unavoidable; children could become infected by playing in a public play area, even if their family did not own a cat.

This is because the T. gondii parasite can survive in soil for several months.

Is has also been suggested that exposure to cats provides risk in terms of other infectious agents shed by cats or by allergic exposures, since increased levels of childhood allergic reactions have been associated with increased risk of schizophrenia in later life.

The sample in the survey was also not representative of the whole population. NAMI members tended to be middle and upper class socioeconomically and their affected family member tended to be more severely affected than average.

To ascertain whether or not cat ownership in childhood is a risk factor for later-life schizophrenia, further research must be conducted that is able to prove cause and effect. Though the gold standard for evidence-based medicine, a randomised controlled trial would not be possible (we hope) for ethical reasons.

It is thought that schizophrenia is a very complex condition that can arise due to a combination of environmental and genetic factors, so simply owning a cat is unlikely to be a major risk factor for the condition.

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Marriage health claims are inconclusive

Friday June 12 2015

Is marriage good for your health?

“Marriage is more beneficial for men than women,” says The Daily Telegraph, while The Guardian reports: “Divorce not bad for your long-term health”. Both headlines are prompted by a new study looking at the long-term effects of relationships on health.

The study used a UK cohort of people born in 1958, who had their relationship status assessed at various younger ages. At age 44-46, they had examinations, where various health markers where measured, including blood inflammatory and clotting factors, lung function and metabolic syndrome (a collection of risk factors that increases risk of cardiovascular disease). 

Generally, men who never married or cohabited seemed to have the poorest health markers in midlife, compared to men who married and stayed married. Meanwhile, women who married in their late 20s to early 30s tended to have the best health markers in midlife. Strangely, there seemed to be the suggestion that divorcing was “good” for men and women by being associated with reduced risk of metabolic syndrome, compared with staying married.

If you are enjoying (or thought you were enjoying) the single life, then you should take these findings lightly. There is likely to be a complex interaction between personal relationships, health and lifestyle factors, and other life events and influences.

It should also be noted that researchers looked at various health indicators, not actual diseases. Therefore, the study does not provide conclusive answers about how marital status may influence health or the mechanisms behind it.

Where did the story come from?

The study was carried out by researchers from University College London, London School of Hygiene and Tropical Medicine, and London School of Economics and Political Science. The study received funding from the Economic and Social Research Council, and the National Centre for Research Methods node “Pathways, Biosocial Influences to Health”.

The study was published in the peer-reviewed medical journal American Journal for Public Health.

The study was reported widely in the UK media, with some sources focusing on the apparent difference in health outcomes between married men and women, while others discussed the findings relating to divorce and separation.

The reporting was broadly accurate, though the limitations of the study were not discussed. 

What kind of research was this?

This study used data collected from a large ongoing prospective cohort to look at relationship patterns over the course of a lifetime, and how they were associated with health in midlife.

As the researchers say, various studies from different countries have suggested that married people have better overall health than unmarried people. It has also been suggested that somehow changing any health inequalities relating to marital status could improve population health. However, to do this, the mechanisms linking marital status need to be better understood. That is what this study aimed to look into, by examining changes in partnership status over a 21-year period and its association with health indicators in midlife.

The main limitation of this study is that it cannot prove direct cause and effect, or explain the influence that any relationship changes may have been having. There is likely to be a complex interaction between personal relationships and other health, lifestyle and life events and influences.

What did the research involve?

This study used data collected from the British National Child Development Study. This is an ongoing cohort study that included all people born in one week in 1958, and periodically followed them up to adulthood. This study used data collected in four assessments – in 1981 (age 23), 1991 (age 33), 2000 (age 42) and 2002-04 (44-46 years).

Relationship status was recorded at each assessment, and health outcomes measured at the final assessment in 2002-04, when the person had a clinical examination. The markers of health outcomes included looking at inflammatory markers in the blood, measuring lung function, and looking for metabolic syndrome (a collection of risk factors that increases risk of cardiovascular disease). 

In their statistical models looking at how change in relationship status was associated with these various disease markers, they took into account various early life and early adulthood characteristics. This included things such as socioeconomic status and parental occupation, education, health, disability and cognitive status in childhood years.

The overall analysis, including those with complete data, was based on 10,226 people (5,256 women and 4,970 men).

What were the basic results?

The researchers split men and women into six groups, according to their partnership status. The most common group of men (62%) were those who married in their 20s or early 30s and had remained married. For women, 42% married in their early 20s and remained married; the next most common group (23%) married later, in their late 20s or early 30s, but remained married. 

Findings in men

Men who never married or cohabited (accounting for 11% of those studied) had generally poorer health markers compared with the most common group of men who married or stayed married. This included poorer lung function and higher levels of certain inflammatory markers and blood clotting factors. Men who had cohabited but not married (8%) also had poorer lung function than those who stayed married. Meanwhile, the 8% of men who married and then divorced and didn’t remarry were less likely to have metabolic syndrome compared with men who remained married. 

Findings in women

In women, the second most common group, who married in their late 20s or early 30s, had the best health. They had lower levels of a blood clotting factor and better lung function than those who married earlier. Meanwhile, women who married but later divorced (9%) were less likely to have metabolic syndrome than the most common group, who married young and stayed married.

How did the researchers interpret the results?

The researchers conclude: “Partnership status over the life course has a cumulative effect on a wide range of objectively measured health indicators in midlife.”

Conclusion

These findings should be taken quite lightly and should not give cause for concern, regardless of marital status. It is very difficult to draw meaningful interpretations from these findings, with the analyses showing mixed results.

Generally, they found that men who never married or cohabited seemed to have the poorest health markers in midlife, compared to men who married and stayed married. Meanwhile, women who married in their late 20s to early 30s tended to have the best health markers in midlife.

Strangely, there seemed to be the unusual suggestion that divorcing was “good” for men and women by being associated with reduced risk of metabolic syndrome, compared with staying married.

However, this study does not prove cause and effect. There are complex interactions between personal relationships, health and lifestyle factors, and other life events and influences. This study is not able to pull this apart and explain the possible underlying reasons for any links between relationship status and the measured health markers.

Importantly, the outcomes measured are only that – a varied collection of blood inflammatory and clotting factors, lung function and metabolic syndrome. These may increase the risk of, or be associated with, actual diseases, but these indicators are not diseases in themselves. For example, the fact that women who married later had lower levels of a particular blood clotting factor and better lung function than those who married earlier on a single assessment day, does not necessarily mean they are all healthier. These midlife health markers may not be good indicators of this cohort’s future health and disease outlook.

Also, this is a specific cohort of people born in 1958. Their marital status and relationship patterns may not be a good parallel for those from other generations, or from other cultures or countries. For example, people in successively younger generations tend to marry later, or may be less likely to marry than those of older generations.

The findings will be of interest in the fields of human sociology and psychology, and will add to the bulk of existing research looking at how marital status may influence health. However, this study alone does not provide conclusive answers about the nature of any relationship or the mechanisms behind it.

Connecting with other people can improve your mental wellbeing, which could also improve physical health, but we wouldn’t recommend rushing down the aisle based on the results of this study. 

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Facebook and Twitter could be used to help people quit smoking

Thursday June 11 2015

Most young people are active on social media

"Using social media to kick the [smoking] habit means you're 'TWICE as likely to succeed'," the Mail Online reports. A study of a Canadian social media campaign aimed at helping young people quit smoking found it was twice as successful as telephone helplines.

The Break It Off (BIO) campaign compared stopping smoking to getting out of a toxic relationship with a terrible boyfriend or girlfriend, and allowed participants to share their progress on Facebook.

Researchers compared the effectiveness of the BIO campaign with anti-smoking telephone helplines. They conducted a trial involving 238 participants aged 19 to 29 who used one of the two methods to stop smoking. After three months, 32% of BIO participants and 14% of the Smokers' Helpline users had quit the habit for 30 days.

But the analysis was only performed on people who completed a survey and not on all of the participants in the study. This and numerous other biases make the results less reliable.

Still, the arguments made by the researchers are persuasive. Many young people do not have access to a landline, so may be unlikely to use telephone helplines, but most young people in developed nations have a smartphone.

This means anti-smoking campaigns aimed at young people may be more effective if they're delivered via social media rather than traditional media formats, such as print and television.  

Where did the story come from?

The study was carried out by researchers from the University of Waterloo, the University of Toronto, and the Canadian Cancer Society, and was funded by research grants from the Canadian Cancer Society Research Institute.

It was published in the peer-reviewed medical journal, Nicotine and Tobacco Research.

The Mail Online reported this story accurately, outlining the worldwide smoking problem and the potential strength of social media in reaching this target audience. But the story did not explain that the results were biased or point out any of the study's limitations.  

What kind of research was this?

This quasi-experimental study aimed to examine the effect of the Break It Off (BIO) social media campaign to help young adults stop smoking, comparing it with the Canadian Smokers' Helpline.

While this study design is appropriate, a randomised control trial would be better as participants would randomly be assigned to groups, reducing the chance of any possible bias.

Any internet-based research is prone to confounding factors, and in this case there were issues with low study recruitment and high loss to follow-up.

What did the research involve?

The study included young adult smokers aged 19 to 29 years from a number of Canadian provinces. Participants took part in one of two interventions aimed at smoking cessation: the Break It Off (BIO) campaign and the Canadian Smokers' Helpline.

The BIO campaign was run by the Canadian Cancer Society, and aimed to provide support and encourage young adults to "break up" with their smoking addiction. Participants were recruited to use the campaign's website between February and September 2012.

The site guided users through the challenging stages of ending an unhealthy relationship with smoking and provided information on quit methods. Visitors could upload a video of their "break-up with smoking" experience, as well as announce their "break-up status" to friends via Facebook. Three months after registration, participants were emailed a link to an online follow-up survey.

BIO participants received a $10 iTunes redemption code as an incentive for registering and another $15 iTunes redemption code when they completed the follow-up survey.

The researchers compared the campaign to the use of the Canadian Smokers' Helpline before September 2011. This is a telephone-based smoking cessation service. It is an established intervention, and provides smokers who want to quit with information, self-help materials, referrals to other resources, tailored motivational counselling, and proactive follow-up counselling.

The helpline was promoted in the media and through referrals from health organisations and professionals. The follow-up survey was conducted via telephone interview between October 2010 and September 2011.

At follow-up, participants were questioned on the following:

• smoking status
• cigarette consumption
• heaviness of smoking (number of cigarettes smoked per day and time of first cigarette in the morning)
• intention to quit
• use of any cessation aid
• whether they had taken at least one action towards quitting

Seven and 30-day abstinence rates were measured at three-month follow-up for both groups. The helpline participants provided the date of the last cigarette they smoked to determine abstinence at three months based on a seven-month follow-up.

Quit rates were based on those participants who completed the follow-up surveys. For both treatment groups, respondents who completed the follow-up survey but did not provide answers to the prevalence questions were considered to be smokers.

Participants were analysed on an intention-to-treat principle. This means participants were analysed in the groups they had been allocated to, regardless of whether they received or adhered to this intervention. 

What were the basic results?

A total of 238 participants completed the study and were included in the analysis. Follow-up rates were low – 34% for the BIO group and 52% for the helpline.

Differences were found between the groups at the start of the study: users of the helpline were more likely to be female, white and have received a high school education or less.

More participants in the helpline group intended to quit in the next 30 days (81% versus 70%) and were much more likely to be daily smokers (82% versus 59%). BIO users had significantly higher seven-day and 30-day quit rates compared with users of the helpline.

The seven-day quit rate for BIO (47%) was more than double that of the helpline (15%) after controlling for confounding factors such as education, ethnicity, and daily or occasional cigarette use. Quit rates at 30 days were 32% for BIO and 14% for the helpline.

BIO participants were more likely to make a quit attempt during the three-month intervention period (91%) compared with helpline participants (79%). Participants in both groups cut down the number of cigarettes smoked – 89% of BIO participants versus 79% in the helpline group.

Having a post-secondary education or higher and only smoking occasionally was found to be associated with an increased odds of quitting smoking.  

How did the researchers interpret the results?

The researchers concluded that, "A large number of young adults prefer a forum such as BIO for help to quit smoking in comparison to traditional quitline services.

"The reach of the campaign and findings on quitting success indicate that a multi-component digital and social media campaign offers a promising opportunity to promote smoking cessation." 

Conclusion

This quasi-experimental study compared the effects of two smoking cessation interventions. The study reported that the use of social media and multi-component digital interventions is more effective in promoting smoking cessation than traditional quitline services.

However, the researchers based their findings solely on the people who completed the final surveys, which will bias the results. This study has a number of other limitations, including the non-random assignment to study group, small sample size, and large loss to follow-up.

The studies were also performed at different time points, which may have affected the results, and some of the BIO participants may also have used the Smokers' Helpline and vice versa. The BIO participants also received incentives for participation, adding more potential for bias.

A very specific target group was included in the study. While this does reduce generalisability, young adults in Canada have the highest rate of smoking, but their use of cessation services is low.

The results of this study are promising and address a major public health issue. A much larger-scale trial needs to be carried out with a longer follow-up period, random allocation, and sub-group analysis for all possible social media and digital platforms to assess which are the most effective in aiding smoking cessation.

As the researchers discuss, smartphone ownership is expected to reach five billion people by 2025. Campaigns based on smartphone use, including social media, are likely to reach a wide audience, as well as be more cost effective.

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Does your birthday affect your disease risk?

Wednesday June 10 2015

Seasonal factors such as vitamin D could have some small influence

"Scientists Find Surprising Link Between Birth Month And Disease Risk," the Huffington Post reports. Using data mining techniques on 1.7 million electronic medical records, US researchers found an association between birth month and certain chronic diseases, as well as less serious conditions such as insect bites.

Fifty-five diseases were found to be associated with birth month – 19 were previously reported in the literature, 20 were for conditions with close relationships to those previously reported, and 16 were new associations.

The newly found associations were a mixed bag, ranging from various cardiovascular diseases (such as high blood pressure and heart failure) and prostate cancer, to incidents such as bruising and insect bites.

The researchers speculate, based on the findings of other studies, why seasonal factors may contribute to specific disease risk, suggesting it could be the result of exposure to antigens such as pollen, varying vitamin D levels, and possibly how old a child is when they first start school. Many unmeasured factors may also be involved in any links.

Overall, this study is not proof that being born in a particular month means you are more or less likely to develop any particular disease. 

But there are effective ways you can reduce your risk of developing chronic diseases in later life. These include stopping smoking, drinking alcohol in moderation, and maintaining a healthy weight through diet and exercise. These steps should help keep your cholesterol and blood pressure at a healthy level. 

Where did the story come from?

The study was carried out by researchers from Colombia University and was funded by National Library of Medicine training grants.

It was published in the peer-reviewed Journal of the American Medical Informatics Association. The study has been published on an open access basis, so it is free to read online or download as a PDF.

This story was covered widely by the press. Most sources took a light-hearted, tongue-in cheek approach, with the Metro saying: "It's still not fully understood why this should be – but just to cheer you up, here's a calendar of the diseases you're at increased risk of, depending on when you're born." 

What kind of research was this?

This modelling study aimed to explore the relationship between season or birth month and lifetime disease risk.

The researchers carried out their study using health record data collected from a large US medical centre database. They say similar studies have focused on looking at associations with specific diseases, so sometimes do not look at rarer diseases.

For this reason, they didn't carry out this research with any particular theory in mind, but just aimed to look at any associations found when looking at millions of records.

This large-scale analysis of massive chunks of data is often referred to as data mining. Data mining is now widely used thanks to improvements in the speed and capabilities of modern computers.

Such a study is good for looking at associations on a large scale, as it can encompass a large number of diseases.

But without testing any particular theory – such as exposure X increases your risk of disease Y – the study can only give us observations and associations. These may not be causative links, and many other unmeasured factors may be involved in any of the links found.  

What did the research involve?

The researchers called their approach the Season-Wide Association Study (SeaWAS), an algorithm looking for diseases with seasonal associations.

They used health record data from the Colombia University Medical Center, where diseases were recorded using standard disease codes (International Classification of Diseases version 9, ICD-9) that were then mapped to specific codes developed for this database (Systemized Nomenclature for Medicine-Clinical Terms, SNOMED-CT).

This coding method is said to capture more medical information than ICD-9 codes and is designed to be transferable across institutions, which will enhance data sharing.

All data was extracted for individuals born between 1900 and 2000 – 1,749,400 people – who were treated at the Colombia University Medical Center between 1985 and 2013. The average age (median) was 38 years.

Analyses were performed to check whether yearly and sex-based variation in the birth month distribution would affect the results. This was found to be minimal.

Associations were investigated between birth month and all recorded conditions. A control group of randomly sampled individuals from the same population without any disease was used to compare monthly birth rate between the case and control populations for each condition.

The study was supplemented by a search of the literature to identify other studies that also looked at links between birth month and disease to see how the SeaWAS findings compared. 

What were the basic results?

The researchers found 55 diseases that were significantly dependent on birth month. Nineteen diseases had been reported in the literature – 20 were for conditions with close relationships to those reported, and 16 were previously unreported.

The 16 previously unreported associations included nine with cardiovascular conditions, such as atrial fibrillation, high blood pressure and heart failure. The remainder included a mixed bag of other conditions, ranging from prostate cancer to coughs, colds and sexually transmitted infections, and bruising and non-venomous insect bites.

Overall, most disease associations were found with October births and the fewest were with May births. Asthma was most associated with July and October babies, and attention deficit hyperactivity disorder (ADHD) with November. March births had most associations with heart problems and winter births with neurological problems. 

How did the researchers interpret the results?

The researchers concluded that, "SeaWAS confirms many known connections between birth month and disease, including: reproductive performance, ADHD, asthma, colitis [bowel inflammation], eye conditions, otitis media (ear infection), and respiratory syncytial virus [a common cause of chest infection in young babies]."

They went on to state they discovered 16 associations with birth month that had never been explicitly studied previously, nine of which were related to cardiovascular conditions. 

Conclusion

This modelling study used a large US medical centre database to explore the relationship between month of birth and lifetime disease risk. The study found a number of associations between birth month and risk of disease, some of which had been previously reported in the literature, as well as other new associations.

While these findings are of interest, this study can only demonstrate observations and associations. The study does not provide proof that being born in any particular month is the direct cause of any future disease development.

There may be many unmeasured factors behind any associations between disease risk and birth month. The study has not been able to look into interactions or explore the lifetime genetic, medical, lifestyle or environmental influences on any individual.

Though the study had strengths in that it used a large medical database where conditions were coded according to a valid system, this is data from just one source. The findings are representative of people from only one region in the US, and they may not be generalisable to other regions or countries.

The researchers addressed this issue and state that the effects observed are likely the result of the climate effects of the region, saying their findings would be most comparable to northern European climates. The researchers hope that lifestyle and diet recommendations can be made once associations are drawn.

But the media reporting of this study, which suggests the month you're born in is a way to predict how you will become ill or die, should be taken very cautiously at this stage. Future research will be needed to see if the same links are observed in studies conducted in different regions, and then explore possible reasons behind these associations.

For now, this study does not provide proof that being born in a particular month means you are more or less likely to develop any particular disease.

There is nothing you can do about the month you were born in, but you can take steps to reduce your risk of disease in later life: have a healthy diet, take regular exercise, avoid smoking, moderate your alcohol intake and maintain a healthy weight.

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Five-year 'death test' for older adults launched online

Thursday June 4 2015

The test uses data gathered by the UK Biobank

"Are you dying to know? Scientists develop death test to predict if you'll make it to 2020," The Daily Telegraph reports. The test is based on analysis of data collected from the UK Biobank.

This is essentially a huge ongoing cohort study that collected data from almost 500,000 middle- to older-age adults in the UK over an average of five years. This data was then used to create an online death risk calculator.

The researchers looked at around 650 different measurements, including blood tests, family history, health and medical history to work out which were most strongly associated with risk of death over the next five years.

This was then used to create an online risk calculator of death. For this, the researchers focused on factors that were easy for people to self-report. For example, you probably have no clue what size your red blood cells are or what your cholesterol level is, but you do know how many children you have.

The factors included in the tool do not necessarily cause death, but are associated with an increase in risk. Many of these factors cannot be changed, such as already having a longstanding illness, but some can be, such as smoking – the strongest predictor of death in people with no medical illness.

Researchers hope the calculator may motivate people to make improvements to their health, or help doctors identify people who could be targeted for interventions to reduce their risk. Studies will be needed to assess whether the tool does lead to these effects.  

Where did the story come from?

The study was carried out by researchers from the Karolinska Institut and Uppsala University in Sweden, and was funded by the Knut and Alice Wallenberg Foundation and the Swedish Research Council.

The Knut and Alice Wallenberg Foundation is the largest private financier of research in Sweden, and their goal is to "promote scientific research, teaching and education beneficial to the Kingdom of Sweden".

The study used data from the UK Biobank, a registered charity set up in the UK by The Wellcome Trust, the Medical Research Council, the Department of Health, the Scottish Government, and the Northwest Regional Development Agency, with additional funding from the Welsh Assembly Government, the British Heart Foundation and Diabetes UK.

The study was published in the peer-reviewed The Lancet on an open access basis, so it is free to view online.

Most of the UK media described the questions included in the online prediction tool UbbLE (UK Longevity Explorer). They also provided expert opinion that highlighted hopes the tool may help people make healthier lifestyle choices, but also pointing out that most of the predictive factors used in it do not directly cause disease.

But some of the reporting of this study by some news sources suggests the online calculator predicts if you'll die within five years – this is not the case. The test does not categorically tell you whether you will die or not, it only gives you a percentage chance based on your characteristics.  

What kind of research was this?

This research used data from a large cohort study of middle- and older-age people from the UK. The researchers wanted to work out the association between multiple measurements of health and socioeconomic status and risk of death over the next five years.

They also planned to create an online tool using the strongest predictors that could be self-reported to allow people to assess their individual risk.

As the analysis is based on a cohort study, the results do not prove cause and effect, and this was not the aim of this particular study. It wanted to identify predictors of risk of death, not necessarily things that cause death directly. 

What did the research involve?

The researchers used information from the large prospective UK Biobank cohort study. By collecting data on the cohort over many years and allowing scientists access to this information, the Biobank aims to improve the prevention, diagnosis and treatment of a wide range of serious and life-threatening illnesses, including cancer, heart disease, stroke, diabetes, arthritis, osteoporosis, eye disorders, depression, and forms of dementia.

UK Biobank recruited 500,000 people aged 40 to 69 into the study between 2006 and 2010. The participants filled out questionnaires and had numerous baseline measurements taken at one of 21 assessment centres across Scotland, England and Wales. In all, there were 655 measurements, which were grouped into 10 categories:

• blood tests
• cognitive function
• early-life factors
• family history
• health and medical history
• lifestyle and environment
• physical measures
• psychosocial factors
• sex-specific factors
• sociodemographics

The researchers used information for 498,103 people and identified any of those people who died up to February 2014, or December 2012 for Scottish participants. Central NHS registers were used to obtain cause of death.

The researchers then analysed the 655 measurements separately for women and men to determine their association with risk of death over the five years of follow-up.

They also calculated the association between each measurement and risk of death for three different age groups:

• 40 to 53 years old
• 53 to 62 years old
• over 62 years old

The risks associated with all 655 measurements were then displayed for women and men on the UbbLE website on pages called the association explorer.

The researchers used the measurements showing the strongest association with risk of death that could be self-reported to create an online mortality risk calculator. This meant excluding any blood tests or physical measurements that a person could not easily, quickly and reliably take themselves.  

What were the basic results?

A total of 8,532 people died during the study period, about 1.7% of participants. This was lower than that of the general UK population, which might suggest the people who took part were generally healthier than the population as a whole.

The most common causes of death were:

• cancer (53% of male and 69% of female deaths)
• cardiovascular diseases, such as a heart attack or coronary heart disease (26% of male and 13% of female deaths)
• lung cancer in men (10% of male deaths, 546 cases)
• breast cancer in women (15% of female deaths, 489 cases)

The strongest predictor of death over five years was:

• self-reported health in men
• a previous history of cancer in women

Other examples of strong predictors of death from various categories included:

• self-reported walking pace – for example, men aged 40 to 52 reporting a slow pace had a 3.7 times higher risk of dying within five years than those who reported walking at a steady average pace
• red blood cell size
• pulse rate
• forced expiratory volume in one second (as a measure of lung function)

When the researchers excluded people with serious illnesses, smoking was the strongest predictor of death.

From these results, the researchers created a prediction tool based on 13 questions for men and 11 questions for women. Based on a person's responses and death rates for the general UK population, the tool estimates how likely a person is to die in the next five years. 

How did the researchers interpret the results?

The authors concluded that, "The prediction score we have developed accurately predicts five-year all-cause mortality and can be used by individuals to improve health awareness, and by health professionals and organisations to identify high-risk individuals and guide public policy." 

Conclusion

This large study has identified numerous risk factors associated with a person's risk of death within five years. Researchers used this information to develop an online tool that predicts someone's risk of death within the next five years. The study's strengths include its large sample size and the prospective nature of the study design.

But there are some limitations. There may be some bias in the type of people who volunteered to take part. The death rate was lower than that of the average population in this age group, which may indicate that the participants were more interested in their health and so had healthier lifestyles. This may limit whether the results apply to the population as a whole.

The study only included people from the UK between the ages of 37 and 73, and results may not apply to people outside that age range or from other countries. For example, the data is reliant on self-reporting, and people from other age groups or countries might interpret some of these concepts differently. This may not be an issue for some factors, but it might be an issue for others, such as estimating walking pace or level of health.

This study did not aim to assess whether the factors directly increased risk of death – rather, it set out to identify factors that are associated with and can predict death risk when combined.  Also, several factors in the calculator cannot be changed, such as current and past health. But smoking – a factor that can be altered – was the factor most strongly predictive of death over the next five years.

As the media pointed out, other aspects of an unhealthy lifestyle, such as poor diet, excess alcohol intake and being overweight, are not included in the online risk calculator.

This is most probably because other factors had stronger associations and were chosen because it made completing the risk questionnaire easier, so overall this would give a better indication of risk. Questions in the risk calculator, such as, "In general, how would you rate your overall health?" are affected by multiple factors, such as obesity and alcohol intake.

The authors say they hope the online tool may help people make positive lifestyle changes. However, they also acknowledge that online health information may increase overdiagnosis and anxiety. Follow-up studies are needed to determine the effects of the calculator – for example, to what extent it motivates people to change their lives and what impact this has.

Overall, one message the study highlights is the importance of stopping smoking. Find out how you can quit smoking.

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Can a single-shot therapy session cure insomnia?

Wednesday June 3 2015

For insomnia, CBT aims to change unhelpful thoughts and behaviours

"Insomnia could be cured with one simple therapy session, new study claims," The Independent reports. UK researchers have been looking at whether cognitive behavioural therapy (CBT) delivered in a single one-hour session can combat acute insomnia.

CBT is a type of talking therapy that uses a problem-solving approach to tackle unhelpful patterns of thinking and behaviour. For example, many people with insomnia develop feelings of anxiety and stress related to not being able to sleep, which can make the problem worse – a vicious circle.

A course of CBT is already an established treatment for insomnia, but this trial aimed to see whether a single one-hour session of CBT could be effective.

Forty adults with short-term insomnia (less than three months) were randomised to a single CBT session or waiting list (no treatment) as a control. Four weeks later, 60% of the CBT group had "remission" of their insomnia (defined as falling below a pre-specified level of insomnia severity on a sleep index) compared with 15% of the control group.

The results show promise, but this was a small sample size who may not be representative of all people with insomnia. The study also had a short follow-up period and it is unknown whether these effects would be sustained beyond a month after the session.

Importantly, brief-form CBT was only compared with no treatment and not with a longer course of CBT or another treatment. A similar trial would be required to see how the brief intervention compares with the alternatives.  

Where did the story come from?

The study was carried out by researchers from Northumbria University, Newcastle University and the University of Pittsburgh in the US.

It was not reported to receive any external funding. One of the authors reports receiving educational grants from UCB Pharma and Transport for London, and has consulted for the BBC.

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

In general, the media has been overoptimistic at this stage. While the results of this small study into the use of a single CBT session for insomnia are promising, questions remain and more study is needed.

Even just going on the results of this study alone, the treatment can't be described as a "cure", despite some media headlines. Not all people showed improvement and we don't know whether the effects lasted longer than a month in those who did improve. 

What kind of research was this?

This was a randomised controlled trial (RCT) that aimed to examine the use of a single session of cognitive behavioural therapy (CBT) for insomnia. CBT is a type of talking therapy that examines thought and behaviour patterns and beliefs and attitudes, and helps people find ways to cope with things by looking at them differently.

Up to 15% of the population are reported to suffer from chronic insomnia, though many more report problems with sleeping. Standard CBT for insomnia usually involves sessions delivered over six to eight weeks and has been demonstrated to be effective.

However, people sometimes have difficulties sticking to long treatment courses, and access to qualified therapists can be limited in some parts of the country.

This study aimed to look at the effects of a single session of CBT for insomnia, accompanied by a self-help booklet, compared with a no treatment or waiting list control condition. This treatment was specifically targeted at people who had insomnia for only a relatively short period of time – less than three months. 

What did the research involve?

The study recruited people with short-term insomnia, and randomised them to a single session of CBT with the accompanying self-help booklet or waiting list control. Researchers then compared participants' insomnia four weeks later to assess the effect of CBT.

Potential participants were recruited from the north-east of the UK and were assessed to see whether they met diagnostic criteria for acute insomnia (duration of less than three months).

Participants also had to have not previously tried CBT for insomnia and not be taking sleeping medications. A total of 40 adults (average age 32, 55% female) were enrolled who had varying underlying causes for their insomnia.

Most (31 out of 40) reported some form of non-medical stress as a cause (such as family, relationship or work problems) and the rest had insomnia related to health problems such as sleep apnoea or depression.

In the group randomised to treatment, the CBT session lasted for around one hour and was delivered on a one-to-one basis by a single experienced therapist.

The therapy included education on sleep and changes in sleep needs throughout life to challenge any misconceptions, and examination of the person's sleep diary, which they had completed when they enrolled in the study. From this diary, the researchers worked out each individual's "sleep efficiency" – the percentage of the time they spent in bed trying to sleep that they actually spent asleep.

The focus then moved to what was called "sleep-restriction titration", where the person was directed about changing time in bed according to sleep efficiency. This involved reducing time in bed by 15 minutes if a person had less than 85% sleep efficiency, increasing it by 15 minutes if they had more than 90% sleep efficiency, and not changing if sleep efficiency was 85-90%.

Sleep diaries were again assessed at one week and four weeks after the session, and at four weeks participants also completed the Insomnia Severity Index (ISI).

This index measures the nature, severity and effects of insomnia on a scale, with each question response ranging from 0 (not a problem) to 4 (a severe problem).

The total possible test score is 28, with a higher score showing more severe insomnia. People whose scores reduced to 10 or less were considered to be in "remission" from insomnia.

People in the "waiting list" control group received no treatment during the study. At the end of the four-week study, participants in both groups were offered a full course of CBT for insomnia.  

What were the basic results?

At the start of the study, there was no difference between the two groups on any characteristics or their ISI scores (average score 14.6 points).

At four-week follow-up, there was a significant difference in ISI scores between the groups. Average ISI score was 9.6 points in the CBT group and 12.7 points in the control group. Remission of insomnia according to the ISI score was achieved by 60% of the treatment group (12/20) compared with 15% of the control group (3/20).   

When examining the sleep diaries, outcomes were also better for the CBT group compared with the control group. The CBT group had significant improvements in how long it took for them to get to sleep (sleep latency), how often they woke after falling asleep, and sleep efficiency. 

After the study, 70% of people in the control group (14/20) requested a full course of CBT, compared with only 5% in the treatment group (1/20). Forty percent of the treatment group (8/20) requested a single booster CBT session, mainly so they could talk about ways to prevent relapsing. 

How did the researchers interpret the results?

The researchers concluded that, "This single session of cognitive behavioural therapy for insomnia is sufficiently efficacious for a significant proportion of those with insomnia."

They say there may be the possibility of introducing this brief form of CBT into the "stepped care model" for insomnia, where people start with lower-intensity treatments and move on to more intense treatments if these don't work.  

Conclusion

This RCT demonstrates that a single one-hour session of CBT led to remission at one-month follow-up for 60% of people with acute insomnia, compared with 15% with a waiting list control.

A course of six to eight weeks of CBT is already a recommended treatment for insomnia, and the results of this study suggest promise for a briefer intervention. This may be better if it makes it more likely people will accept treatment and stick with it. Shorter sessions would also be easier to provide, as they need fewer resources.

However, there are important points to bear in mind before taking this study as conclusive proof of the effectiveness of a single CBT session for insomnia:

• The study was small, involving only 20 people in each of the treatment and waiting list control groups. The results need to be confirmed in a much larger trial. 
• These were a specific group of people: young adults (average age 32) who had insomnia lasting for less than three months (mostly as the result of work or relationship stress) who were all willing to take part in the study and try CBT. They were also not taking any sleep medications. Results in this group may not apply to other types of people who have insomnia, so care should be taken when generalising to populations, such as those with chronic sleep problems and the elderly.
• Follow-up was only for one month. We don't know if there would be a lasting effect or whether further booster sessions would be needed to maintain effectiveness.
• Comparison was made to a waiting list control – people who received no insomnia treatment and knew this. These people may not have been happy with the fact they were not receiving treatment and this could affect their rating of their insomnia. Also, we can't say how single-session CBT performs compared with alternatives. Ideally, a trial would need to compare the short version of CBT with the full course or other alternatives to compare their effects.
• The researchers say the number of requests for a full course of CBT at the end of the study was "used as a gross indicator of treatment acceptability". The majority of people in the control group wished to have a full CBT course, but only one of the treatment group wanted a full course. It is difficult to know what to interpret from this – for example, whether people in the CBT group didn't find it acceptable to be treated for longer and wanted no further CBT, or whether they felt they'd already gained enough benefit. However, the fact 8 out of 20 wanted a booster session may suggest they didn't feel the need for a full course and preferred to have another brief session.

Overall, the research suggests promise for brief CBT interventions for insomnia, which may well have a place in the treatment of the condition.

However, at this stage questions remain and larger studies are needed, particularly in comparison with other treatments, such as a full treatment course of CBT.

If you are affected by persistent insomnia, self-help techniques, such as not drinking tea, coffee or alcohol in the evening and taking daily exercise of at least 30 minutes a day, may help.

If the problem persists, see your GP. There may be an underlying medical condition contributing towards your sleep problems. Your GP can also refer you to a CBT therapist. 

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