Could cannabis damage DNA that is then passed down generations?

Thursday May 26 2016

One of the active ingredients in cannabis may damage DNA

"Smoking cannabis can alter a person's DNA, causing mutations that expose a user to serious illnesses," the Mail Online reports.

A new review has looked at the role cannabis may play in what is known as chromothripsis.

A relatively recent discovery, chromothripsis is when the DNA of a cell suffers large-scale damage, but not enough to kill the cell. It has been linked to some types of cancer and birth defects.

In this review, researchers considered the evidence about whether one of the active ingredients in cannabis – tetrahydrocannabinol (THC) – could trigger chromothripsis, which could potentially cause cancer and other illnesses.

The researchers also raised the possibility that the DNA damage could be passed down to later generations.

There is a great deal of uncertainty about how the included studies were chosen, so there is a possibility not all relevant research was considered.

This type of study serves to stimulate debate and further research. It is not reliable enough to form the foundation of policy change on its own.

Arguably, a longer-term study would be needed to see if cannabis use could have an intergenerational effect.

We do know that cannabis, a class B illegal drug, is known to contain cancer-causing chemicals (carcinogens) and has previously been linked with lung cancer, psychosis, schizophrenia and fertility problems.

Find out more facts about cannabis.

Where did the story come from?

The review was carried out by two researchers from the University of Western Australia. There was no external source of funding.

It was published in the peer reviewed journal, Mutation Research: Fundamental and Molecular Mechanisms of Mutagenesis.

The Mail Online's headline, "Smoking cannabis can alter a person's DNA, causing mutations that expose a user to serious illnesses", made it sound like the researchers' hypothesis was proven by newly uncovered evidence, which is not the case.

The headline and article did largely reflect the researchers' findings, but failed to add any notes of caution, balance or discussion about the limitations of the research, instead taking it at face value.

What kind of research was this?

This was an evidence-informed narrative review of research exploring the hypothesis that cannabis use causes errors in human DNA, potentially leading to cancer and affecting brain development in unborn babies.

Non-systematic reviews like this are useful for summarising scientific research in a particular area, but can miss relevant research and counter-arguments.

Without a clear and systematic review of the published and unpublished science, there is a risk the authors cherry-picked the evidence, consciously or unconsciously, to fit their views. 

Such a one sided-argument has its place in stimulating debate, but should not be viewed on a par with a systematic review, one of the highest levels of evidence.

A systematic review of well-designed long-term cohort studies would be one of the best ways to assess the causal links between cannabis and DNA damage and disease.

What did the research involve?

The research is a narrative review of evidence that presents the idea that cannabis can disrupt a person's DNA, potentially raising their risk of cancer and causing genetic toxicity that could be passed from one generation to the next.

The review assembled data from 189 research articles. However, it had no reported methods. As such, we cannot assume the researchers employed systematic review methodology.

As the authors didn't mention how they found the articles, the study risks being biased to fit a coherent story, or may have missed other relevant research.

Some limitations in the evidence were presented, although quite briefly. The relative strength and balance of evidence for and against their hypothesis is not clear.

What were the basic results?

The review starts by providing scientific background on key moments in cell division – a complex and crucial process of normal cell growth and tissue maintenance.

It then outlines evidence that cannabis disrupts this process at specific points, leading to potentially cancer-causing DNA mutations.

This is a relatively recent discovery known as chromothripsis, which in a literal Greek translation means "chromosomes shattering into pieces".

Some of the main points revolve around the effects of cannabis on cancer and foetal abnormalities.

It also touches on the possibility that genetic mutations may be passed down through generations – meaning a child who has never touched cannabis could be negatively affected because of their parents' past use.

Cannabis and cancer

The review describes several observational studies linking cannabis to cancer, including brain, prostate and lung. Many also showed the higher the cannabis use the higher the cancer risk, a tentative sign of causation.

The authors acknowledge that other studies showed no link, but suggest this might be because the participants were quite low cannabis users, making a link easier to detect, or that the link only exists after a certain threshold is passed.

For example, one study reported "heavy cannabis use" as more than 0.89 joints in one day, which may not have been enough to cause DNA damage.

Cannabis and foetal abnormalities

The review discusses several studies showing a positive link between cannabis use and foetal abnormalities such as spina bifida or low birth weight as a result of disruptions in cell growth.

As before, the authors pointed out that harms were generally found when cannabis use was high (around 50-300mg/kg) – although the definition of this was variable. 

Other addictive substances

The review says that the effects of other addictive substances – alcohol, opioids, tobacco and benzodiazepines – on the development of tumours and foetal abnormalities are similar to cannabis. In other words, they all disrupt the cell cycle in a similar way.

The harmful link between alcohol consumption and tobacco use during pregnancy has long been known.

Cannabis use and future generations

Transmission of cannabis-related genetic damage from parent to child has been shown in rat and human studies, as well as for damage caused by alcohol, cocaine and opioids.

As this type of research has only just scratched the surface, the review authors said it was "an exciting time" for continuing research in this area.

How did the researchers interpret the results?

The researchers concluded that cannabis use was likely associated with cancers and other serious illnesses because it causes DNA damage in a person's cell during and around cell division.

The authors highlighted that this was an important finding as the use of cannabis is increasing globally, as is the strength of cannabis, while many countries are starting to legalise its use.

Conclusion

This review presents a useful summary of evidence backing the idea that cannabis can disrupt cell division, causing genetic damage, potentially leading to the development of cancer and foetal abnormalities.

The review was transparent in exploring the evidence behind one theory. And while this is a valuable body of research, a systematic review would have been more reliable, providing a more balanced view of the evidence.

Because of the uncertainty about how the included studies were chosen, there is a possibility that not all the relevant research was considered.

The strength of the included evidence was also not discussed. So we don't know whether it was generally strong or weak, or how it stacks up against counter-evidence. Results are only as good as the studies included, and this can vary depending on study design and assessment.

This type of study serves to stimulate debate and further research. It is not systematic or reliable enough to form the foundation of policy change on its own.

Read more about the potential harms of cannabis use.

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Healthier lifestyles 'could cut cancer death rates'

Friday May 20 2016

A few hours exercise a week can cut cancer risks

"Half of all cancer deaths could be avoided if people simply adopted a healthier lifestyle," the Daily Mail reports.

A new study adds to the weight of evidence that says combining simple lifestyle changes can dramatically cut cancer death rates.

More than 100,000 health professionals from the US were asked to complete questionnaires about their lifestyle and cancer status every two years, and diet every four years.

The researchers compared cancer rates between people with low- and high-risk lifestyle factors, and also compared rates in the low-risk group with the general white population in the US.

They found a large number of cancer cases and deaths could be attributed to a high-risk lifestyle, such as an individual being overweight, smoking, drinking heavily, or being physically inactive.

The researchers estimated between a quarter and a third of all cancer cases in this population group could be attributed to poor lifestyle factors.

These findings are in agreement with past research and the understanding that a healthier lifestyle may reduce the risk of various types of cancer.

But this study has limitations, including the population group, which only involved white American health professionals, and the possibility that the estimates are inaccurate. 

The study would appear to confirm that any small lifestyle changes you can make, such as quitting smoking, could considerably reduce your risk of developing cancer. And the more of these small changes you can combine, the greater the effect.

Read more about how lifestyle changes can help prevent cancer.

Where did the story come from?

The study was carried out by researchers from Harvard Medical School and was funded by the US National Institutes of Health.

It was published in the peer-reviewed journal, JAMA Oncology.

The Daily Mail reported on the study fairly accurately, but did not present any of its limitations.

It's nice to see that the article included clear recommendations from the research team about how a person can reduce their risk of cancer.

However, the headline figure of "half of all cancer deaths" seems a bit of a fudge, as the study presented a range of different results for specific cancer types.

What kind of research was this?

This prospective cohort study followed a large population group over time, and assessed the incidence of cancer and related deaths.

The researchers looked at how these cancer outcomes were related to various lifestyle factors, and then estimated the proportion of cancers that could be attributed to these factors.

The observational nature of this type of study means it is not able to prove causation, but it can find links and potential risk factors.

This type of study has strengths in terms of being able to follow a large number of participants over a long period of time, but the number of people who become non-responsive to follow-up assessments may increase over the years.

What did the research involve?

The researchers recruited participants from two cohort studies:

• The Nurses' Health Study – which started in 1976 and enrolled female nurses aged 30 to 55
• The Health Professionals Follow-up Study – which started in 1986 and enrolled male health professionals aged 40 to 75

Participants completed questionnaires about their medical history and lifestyle at the beginning of the study and every two years thereafter. Dietary information was collected every four years using a validated food frequency questionnaire.

The researchers split the participants into two groups according to the level of health risk associated with their lifestyle.

To be considered low risk, a participant had to meet the following requirements:

• have never smoked or be a past smoker more than five years ago
• drink no or a moderate amount of alcohol – no more than one drink a day for women and two for men
• have a body mass index (BMI) of at least 18.5 and lower than 27.5
• do at least 75 minutes of vigorous-intensity or 150 minutes of moderate-intensity aerobic physical activity a week

If all of these requirements were not met, the participant would be considered high risk.

The outcomes of interest were the incidence of total and major individual cancers and associated deaths. Cancer was self-reported in the questionnaires. Where a participant failed to respond, the National Death Index was used to identify deaths.

The researchers compared the cancer rates between the low- and high-risk groups. They then compared cancer rates in the low-risk group with cancer rates in the general population using national surveillance data.

They used this information to help them calculate population-attributable risk (PAR).

This is an estimate of the proportion of all cancer cases that can be attributed to poor lifestyle factors, or the number of cancers that would not occur in a population if the risk factor – in this case, a high-risk lifestyle – was eliminated.

For example, a PAR could be used to estimate how many people in a given population would not die of lung cancer if nobody in that population smoked.

What were the basic results?

A total of 135,910 people were included in the study (89,571 women and 46,339 men). The low-risk group contained 21% of all participants (12% women and 9% men) with the remaining 79% classed as high risk (54% women and 25% men).

The incidence of cancer per 100,000 people was 463 for women and 283 for men in the low-risk groups, compared with 618 for women and 425 for men in the high-risk groups.

From this, the researchers estimated that 25% of cancers in women and 33% of cancers in men could be attributed to high-risk lifestyle factors. For cancer-related deaths, 48% of cancer deaths in women and 44% of cancer deaths in men could be attributed to a high-risk lifestyle.

For individual cancers, the proportion of cancers estimated to be caused by high-risk lifestyle factors were:

• lung – 82% for women, 78% for men
• bowel – 29% for women, 20% for men
• pancreas – 30% for women, 29% for men
• bladder – 36% for women, 44% for men

Estimates were similar for cancer death, though there were additional associations for some other sites, including breast (12%), womb (49%), kidney (48% in men), and oral and throat (75% in women and 57% in men) cancers.

The general US populations were at higher risk than the whole study population, meaning that the PARs for these cancers resulting from a poor lifestyle were even higher than the researchers' estimates – for example, the PAR for bowel cancer jumped to 50%. 

How did the researchers interpret the results?

The researchers concluded that, "In this cohort study of a portion of the US white population, about 20-40% of cancer cases and about half of cancer deaths can be potentially prevented through lifestyle modification.

"These figures increased to 40-70% when assessed with regard to the population of US whites, and the observations are potentially applicable to broader segments of the US population." 

Conclusion

This prospective cohort study assessed the number of cancer cases and related deaths associated with poor lifestyle factors in a sample of US health professionals.

As the findings demonstrate, a large number of cancer cases and deaths in both men and women can be attributed to a high-risk lifestyle, such as being overweight, smoking, drinking heavily, or being physically inactive.

Worryingly, a poor lifestyle was estimated to account for an even greater number of cancers in the general population.

These findings are in agreement with much research, which has found that a healthier lifestyle may reduce the risk of various cancers.

The study has both strengths and limitations to consider. It contained a large number of participants and excluded types of cancer where incidence may be related to environmental factors rather than lifestyle, both adding strength to the findings.

It did have limitations, however:

• The use of questionnaires for collecting information is prone to bias, either by people reporting what they think they should be doing rather than what they are doing, or because of difficulty recalling information over a period of time.
• Only medical professionals were included in the study. This group are potentially more health conscious, so may not be a good reflection of the whole population. This is supported by the fact that even the high-risk study group were healthier than the US population overall, and PAR estimates for cancer from poor lifestyle factors were higher in the general population.
• Only including a white population means these findings may not necessarily apply to other ethnicities.
• These results are only estimates: though informed by careful analysis of this population and their lifestyle factors and cancer rates, it's possible that the proportion of cancers attributed to poor lifestyle factors is inaccurate, particularly for wider populations.

Despite these limitations, it is well known that unhealthy lifestyle factors could increase your risk of developing cancer, as well as various other health problems. Any small changes you can make to your lifestyle could considerably reduce your risk.

Read more about how to prevent cancer.

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Are broken bones, loneliness and poor sleep really hidden killers?

Wednesday May 18 2016

A broken bone can affect other areas of wellbeing

"Revealed, the five hidden killers that could send you to an early grave," the Daily Mail reports. These "hidden killers" include loneliness and poor sleep. But this is a simplistic take on complex research aiming to identify new ways of classifying health and wellbeing.

The research assessed the health and lifestyle of 3,000 US adults aged 57 to 85 years, then reassessed how many were incapacitated or had died five years later.

The researchers then compared two models to see which better categorised the participants' health status and risk.

The first mainly looked at the presence of diseases. The second model was more comprehensive, and included wider measures such as psychological wellbeing, mobility and health behaviours.

Overall, two-thirds of the sample was classed as being in "robust" good health when using the medical disease model, but many of these fell into more vulnerable risk groups when using a more comprehensive risk model.

The comprehensive model identified poor mental health, including depression, isolation and memory problems, and frailty and mobility problems as being predictive of mortality – "hidden killers" in newspaper speak – factors that would be largely overlooked if you only focused on physical diseases.

The findings suggest a comprehensive view of a person's health and wellbeing is needed when looking at their risk status and trying to target appropriate medical care and support.

Wellbeing and quality of life is not simply a case of whether or not someone has a physical illness. 

Where did the story come from?

The study was carried out by researchers from the University of Chicago, and was funded by the same institution and the US National Institute of Aging.

It was published in the peer-reviewed journal, PNAS, and the article is openly available for access.

The Daily Mail, The Sun and Metro articles are generally representative of the study's findings on loneliness, fractures and mobility problems.

But none of the papers grasped the point of the study – an attempt to create more complex and subtle models of wellbeing.

What kind of research was this?

This cohort study aimed to look at the best way of defining population health.

The researchers explained how the World Health Organization (WHO) defines health as a "state of complete physical, mental and social wellbeing and not merely the absence of disease or infirmity".

However, despite this there has been little rigorous attempt to use this definition to measure and assess population health. More often, what is described as the "medical model" is used to measure health, which focuses solely on disease diagnoses.

The researchers propose a "comprehensive model" that also considers psychological wellbeing and function as being a better fit to the WHO classification.

The researchers applied both of these models to US survey data to see how population health was defined by the different methods.   

What did the research involve?

The research involved a large, nationally representative sample of 3,005 older US adults aged 57 to 85 years who lived in the community and were taking part in the National Social Life, Health and Aging Project (NSHAP).

The participants were interviewed and completed a questionnaire about their health and lifestyle, as well as having body measures taken.

The researchers then used two different models to categorise the state of a person's health.

The medical model looked at specific diseases:

• heart disease
• cancer
• lung disease
• stroke
• diabetes
• kidney disease
• liver disease
• arthritis
• high blood pressure
• asthma
• thyroid disease

The comprehensive model also included 35 additional measures that encompassed five broad dimensions of health and wellbeing:

• health behaviour – smoking, exercise, sleep
• psychological health – depression, memory
• sensory abilities – vision, hearing
• neuroimmunity – chronic inflammation
• mobility or frailty – including fractures

The researchers followed these people up five years later. They then identified a few distinct health classes or categories within these models that encompassed several of the disease and wellbeing features, and most reliably indicated a person's health and mortality risk.  

What were the basic results?

The researchers identified five distinct health classes within the medical model that had significant and independent effects on mortality.

The first two classes were people who had undiagnosed high blood pressure (hypertension) and a single non-cardiovascular disease. These were the least vulnerable, or most "robust", health groups.

The intermediate (third) risk group were those with poorly controlled diabetes. The two most vulnerable groups (four and five) were those who had both cardiovascular disease and diabetes, or who had extensive medical illnesses.

People in the first two robust classes had around a 15% risk of being physically incapacitated or dead after five years, compared with 35% in the top extensive illness group.   

In the comprehensive model, six distinct classes arose – again, the first two classes were the least vulnerable, or most robust; classes three and four had an intermediate risk; and five and six were the most vulnerable.

The six classes were:

1. robust obese – obese but generally in good health
2. one minor condition – stomach ulcer, thyroid problems, bladder problems
3. broken bones – people with osteoporosis
4. poor mental health – depression, poor memory and loneliness
5. diabetes, hypertension and immobility
6. extensive medical illnesses and frailty

Almost a quarter of this older US population (22%) were in the first robust obese group. These people often had undiagnosed hypertension as measured by a home device, but, other than this, few other diseases and only a 6% risk of dying after five years.

The second group were not obese and had a minor condition – one not considered to have high mortality risk – and a 16% risk of death.

The two middle classes of the comprehensive model – those with fractures or osteoporosis and poor mental health – included 28% of this US population, despite being, as the researchers say, "largely ignored" by the medical model.   

The last two, most vulnerable, classes had the most compatibility with the vulnerable classes of the medical model, but still more people were reclassified as vulnerable when using the comprehensive model.

People in the most vulnerable sixth group had a 44% risk of dying within five years.

Overall, the medical model classified two-thirds of the older US population as being in robust health. Only half of these people went into the robust classes of the comprehensive model.

These findings suggest that factors such as poor mental health, bone fractures, and sensory and mobility problems are very important to consider when categorising vulnerability and mortality risk.

How did the researchers interpret the results?

The researchers concluded that the comprehensive model identifies new classes of people with mortality risk, such as those with broken bones or poor mental health, who are largely overlooked by medical models that only focus on disease.

They said that: "This approach provides a method for broadly reconceptualising health, which may inform health policy", with implications for medical care, prevention and resource allocation.   

Conclusion

As the researchers say, the WHO definition of health encompasses physical, mental and social wellbeing – not just the presence or absence of disease.

But how often are these extra dimensions taken into account when assessing a person's health status?

In this sample of older adults, just looking at their disease status puts the majority of them into an apparently "robust" health group.

Yet when you consider the additional dimensions of psychological health and wellbeing, you seem to get a much better indication of those who were at higher or lower risk of dying or being incapacitated in the coming five years.

The "hidden killers" the media refer to are factors such as frailty and fractures, and depression and loneliness, which would be overlooked if you looked at disease diagnoses alone.  

This suggests that a comprehensive view of a person's health and wellbeing is needed if you are looking at their risk status, and trying to target appropriate medical care and support.

But you can't say from the results of a study like this that these factors are being overlooked within healthcare.

For example, just because a medical risk model looking at physical diseases alone hasn't looked at these factors as a risk indicator doesn't necessarily mean that the people with these conditions have not been diagnosed in medical practice and are not receiving appropriate care and treatment.

The media term "hidden" in this context is therefore a bit misleading – as is the term "killer".

Of course, factors like loneliness and depression aren't necessarily going to lead to death directly, but could be associated with other poor health factors that together contribute to mortality risk.

Although this is a large, nationally representative sample, these are all older US adults. The six predictive classes the researchers identified to indicate robust, intermediate or vulnerable risk status may not be the same if people from another country were examined, or a population of middle-aged or younger adults.

It would be interesting and useful if researchers carried out a similar analysis on various groups within the UK population.

The study is a valuable contribution to how we define health and wellbeing. However, whether it has any direct implications in terms of health assessment, screening and diagnosis is unknown at this stage.  

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Women who regularly attend religious services 'live longer'

Tuesday May 17 2016

Churchgoing women were more likely to be non-smokers

"Going to church could save your life," reports the Daily Mail, adding that, "Women who worship once a week are '25 per cent less likely to die early'."

Perhaps surprisingly, while the first part of the headline is overly simplistic, it may not technically be wrong – according to new research from the US, anyway. Whether or not divine providence is responsible for the increase in lifespan is still up for debate.

A large Harvard study showed that predominantly white Christian nurses who attended religious services more than once a week had a 33% lower relative risk of dying over a 16-year period compared with similar women who did not attend religious services.

A sizeable chunk of the link was explained by social support (23%), smoking rates (23%) and, to a lesser extent, optimism differences (9%) between attenders and non-attenders.

The study was very large, precise, and as robust to bias and confounding as you could reasonably expect, so it can be considered reliable. But the lifestyle and social differences between the groups can't go unnoticed.

It's therefore possible that the regular pattern of social interaction associated with being part of a religious community, and the benefits this brings, is mainly responsible for the outcome seen in this research, rather than any specific religious or spiritual aspects.

Atheists who regularly attend humanist gatherings, or just those who go to weekly bingo sessions, may also experience similar benefits.

Read more about the benefits of connecting with others.

Where did the story come from?

The study was carried out by researchers from the Harvard T. H. Chan School of Public Health in the US.

It was funded by the John Templeton Foundation, which, according to its website, funds research on the "big questions of human purpose and ultimate reality". The foundation has a stated aim of using scientific methods to explore the alleged spiritual aspects of reality.

The study was published in the peer-reviewed Journal of the American Medical Association: Internal Medicine.

Generally, the media covered the story accurately, citing the possible reasons why attending religious services might be good for you in terms of boosting social support, happiness and optimism.

For example, The Independent reported advice from the researchers, who said: "Our results do not imply that healthcare professionals should prescribe attendance at religious services, but for those who already hold religious beliefs, attendance at services could be encouraged as a form of meaningful social participation." 

What kind of research was this?

This cohort study looked at the links between religious service attendance and subsequent death in female nurses.

This type of study is appropriate to investigate this link.

But many factors can influence death rates, and potentially also be linked to church attendance – for example, more resilient social networks can help people cope in times of hardship.

Teasing out any clear causal links from the vast mix of influencing factors is tricky.

What did the research involve?

This study analysed self-reported religious service attendance information from 1996 to 2012 and linked death records from the same time period.

The researchers analysed information from 74,534 female US nurses who had been answering health and lifestyle questionnaires every two years from 1992 to 2012 as part of the Nurses' Health Study, a rich ongoing source of epidemiological research.

From 1992 and every four years thereafter, women were asked how often they go to religious meetings or services. Responses included more than once a week, once a week, one to three times a month, less than once a month, and never (or almost never).

The researchers' main analysis looked at the death rates of women with different frequency of religious attendance, comparing them with those who did not attend.

They adjusted for a lot of confounders to try to isolate the single effect of religious attendance, including:

• age
• alcohol consumption
• physical exercise
• multivitamin use
• high blood pressure
• high cholesterol
• use of hormonal replacement therapy
• healthy eating scores
• smoking status
• body mass index
• husband's education level
• physical impairment
• social integration score – composite of marriage status, group participation, number of close friends or relatives
• living alone
• family income
• geographic region in the US
• depression in 1992
• religious attendance in 1992

The researchers also performed a "mediator" analysis, which helps understand how much each of the confounders is contributing to the main link of interest – in this case, religious service attendance and death.

What were the basic results?

Most women were either Roman Catholic or belonged to other Christian denominations, and 97% or more were white. There was a small minority of Jewish women and no Hindu or Muslim women.

There was a consistent pattern between religious service attendance and lower rates of death from any cause, cardiovascular disease and cancer.

There were 13,537 deaths over the study period, giving a base rate of death of 18.1 %. Compared with women not attending religious services, women who attended a service more than once a week had 33% less risk of dying from any cause during the 16-year study (hazard ratio 0.67, 95% confidence interval [CI] 0.62 to 0.71).

Those attending regularly in both 1996 and 2000 – a sign of long-term, regular attendance – had an even lower relative risk at 45% (95% CI 0.52 to 0.59) less than non-attenders.

Looking at potential mediators, the researchers picked out depressive symptoms, smoking, less social support and optimism as the most important.

Social support explained the highest proportion of the link (23%), with smoking a close second (22%). Optimism accounted for around 9%.

The link appeared consistent over time, as well as for religion (although there wasn't much variety), geography and other potentially influential factors.

How did the researchers interpret the results?

The researchers said that: "Frequent attendance at religious services was associated with significantly lower risk of all-cause, cardiovascular, and cancer mortality among women.

"Religion and spirituality may be an underappreciated resource that physicians could explore with their patients, as appropriate." 

Conclusion

This study showed that white Christian women who attended religious services more than once a week had a lower risk of dying from any cause, cancer, and cardiovascular disease specifically compared with similar women who did not attend religious services.

This link was at least partially explained by social support, smoking rates, and optimism differences between attenders and non-attenders.

As the study was very large, it gives precise estimates of relative risks. The researchers pointed out there are other factors that could potentially mediate the link that they couldn't measure in their study, like psychosocial resilience, religious coping mechanisms, a sense of a purpose in life, and self-discipline.

But their interesting stats also showed that biases from these or other sources would have to be very large to affect the result in a meaningful way, suggesting the study's conclusions are quite solid.

The study mainly involved white women who mostly identified as Christian, so we don't know if the same effects would be seen for men of a similar faith, or adults or children from other religions or with no religion.

Non-religious groups could argue having a purpose in life, self-discipline and many other aspects that potentially mediate the link are not the sole preserve of the religious, but there is no doubt that for many people this comes from practising a faith.

But it's possible the same effect could be achieved in other ways, too. While the researchers tried to account for social factors associated with religious attendance, there could well be other unmeasured, or possibly unconsidered, effects associated with regular social group interaction.

A similar study could have noted reduced mortality among people attending any community activity groups or societies, both for people of all faiths as well as people with none.

As we discussed last month, people with a history of cancer who regularly attended a choir session showed evidence of improved immune function.

Human beings are social animals, so enjoying regular social activities with others is probably a good way, among others, to improve both your physical and mental wellbeing.

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Dad's age, diet and drinking habits may impact on birth defect risks

Monday May 16 2016

Age, diet and drinking can damage sperm quality

"Men are being warned to become fathers by 40 or face a greater risk of having children with serious illnesses," the Daily Mail reports after a new review looked at some of the evidence about paternal influences on the risk of childhood diseases.

The review discusses several research findings found previously, including some reports that children born to fathers over the age of 40 have higher rates of conditions like autism spectrum disorder – and that stress, smoking and alcohol may also cause heritable changes.  

But this is an opinion piece. We don't know how the researchers selected the evidence they reviewed, and it is possible that not all relevant research was considered.

The review should not be taken as firm evidence that there is such a thing as a "male biological clock" and fathers are putting their children at risk by delaying fatherhood until middle age.

Still, men trying for a baby should avoid smoking, excessive alcohol consumption and eating a poor diet. It may not boost your sperm's health, but it will definitely improve your health.  

Where did the story come from?

The study was carried out by researchers from Georgetown University Medical Centre in the US, and was funded by the US National Institutes of Health.

It was published in the peer-reviewed American Journal of Stem Cells. This is an open-access journal, so the study can be downloaded for free as a PDF.

Neither the Daily Mail nor The Times recognise the important limitations of this review: namely, that is it is not a systematic review, so it carries far less weight in terms of evidence.

Also, the Mail talks about men being "warned" about delaying fatherhood – but, as far as we can tell, the only people actually issuing any warning based on this review is the Mail itself.

What kind of research was this?

This appears to be a narrative review discussing whether how a man's age and environmental exposures may alter his genes and so be passed on to his offspring.

The article centred on epigenetics, the idea that, though a person's DNA sequence may not change, their exposures over the course of a lifetime may lead to changes in their gene activity and expression that can be passed on to their children.

This happens through mechanisms such as DNA methylation, where methyl groups (types of molecules) are added to the building blocks of the DNA, or where small RNA molecules (miRNA) are added to the DNA – both of which alter gene activity.

This review discusses how epigenetics in the father have an effect on the offspring, focusing on age and environmental exposures. The researchers discuss these theories, referencing various publications, but this does not appear to be a systematic review. 

The research team did not provide any information about how they identified and selected the evidence they reviewed. As such, it is possible that not all relevant research has been examined and so this must largely be considered to be an opinion piece.      

What does the research say about a father's age?

The researchers say that past research has shown that a father's age has a significant effect on a child's characteristics and the likelihood of them having congenital abnormalities.

Some studies have linked increasing paternal age (over 40 or so years) with higher rates of conditions like autism and schizophrenia. Others have observed increased rates of birth abnormalities, such as heart defects, musculoskeletal abnormalities, and Down's syndrome.

Mouse studies also support this. Studies have shown that mice born to "old" fathers (over two years old) performed poorly on tests of learning and memory, and also had a reduced lifespan and less reproductive success themselves. Mice with slightly younger fathers (10 months old) were less social.

The researchers say that although the mechanism behind this is not established, most evidence points in the direction of DNA methylation. Animal studies have shown higher rates of DNA methylation in the sperm cells of older rats compared with younger rats.

What does the research say about environmental exposure?

The effect of environmental exposures on offspring is less clear, although there is some evidence of this. Some studies have shown that people with little available food have demonstrated some changes that can be passed on to their children, though not necessarily bad ones.

It's reported that children born to fathers who had low food availability during pre-adolescence were less likely to die from cardiovascular disease. And those whose grandparents had little food were less likely to have diabetes.

Other studies have suggested stress induces DNA changes that could be passed on. Mouse fathers who were subject to the stress of food deprivation before mating had offspring with lower blood glucose levels.

Mice exposed to other psychological stressors – such as cage changes and fox smell – had offspring that displayed blunted stress responses, indicating some form of behavioural defect.

Smoking and alcohol may also have effects. Smoking has been shown to alter the DNA in sperm.

And three-quarters of babies with foetal alcohol syndrome – birth defects normally associated with maternal consumption of alcohol during pregnancy – are reported to have fathers with alcohol use problems.

Chronic alcohol use in the father is said to again affect DNA methylation. In rats, offspring from fathers given alcohol were more likely to have a low birthweight or spatial learning problems when put in a maze test.

Studies in mice also found those whose fathers were given alcohol were more likely to have cognitive and mobility problems. 

How did the researchers interpret the results?

The researchers say their review findings support the concept of the epigenetic inheritance of paternal experiences across generations.

They say their review highlights "the possible links between birth defects and paternal age, environmental factors, and alcohol consumption" and the need for future research in this area.

Conclusion

This narrative review summarises past research on DNA changes that may occur as a result of a father's age and exposures that could be passed on to his children.

In particular, the review discusses animal and human studies that have linked changes in offspring with increasing paternal age, stress and substance use.  

But this review must largely be considered to only be an opinion piece. We don't know how the researchers identified, appraised and selected the studies they discussed.

As such, there is a strong possibility that not all animal and human research relevant to the issue of paternal epigenetic inheritance will have been reviewed and discussed here.  

There are also no clear methods or results provided for the studies that are discussed, with only a few brief sentences given for each study. We are not able to critique the quality and strength of evidence linking a father's age or any other exposure with the outcome reported. 

For example, people would likely be concerned by reports that increased rates of autism or congenital defects have been observed in children born to fathers over the age of 40. But we have nothing more to go on than this – no firm risk figures are given.

And the observational studies themselves are likely to have been influenced by various unknown sources of bias and confounding, like the report that three-quarters of babies with foetal alcohol syndrome have a father with alcohol use problems.

This doesn't tell us anything about what the mother is doing. It could be that many of these babies had a mother who also had alcohol use problems – alongside her partner – and used alcohol during pregnancy, and has directly exposed the developing baby.

This study will add to the research on how parental exposures may be passed on to a child through epigenetics.

However, given the limitations of this review and the lack of methods given, this opinion piece should not be taken as firm evidence that fathers are putting their children at risk by delaying fatherhood.

These limitations aside, advice that men hoping to become fathers should avoid known bad lifestyle behaviours, such as smoking, drinking too much, not exercising and eating a poor diet seems sensible.

Read more about what both men and women can do to protect their fertility.

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No evidence probiotics are beneficial for healthy adults

Thursday May 12 2016

It's been claimed probiotics can promote bacterial diversity

"Probiotic goods a 'waste of money' for healthy adults, research suggests," The Guardian reports. A new review of previously gathered data found no evidence that probiotics improved the balance of gut bacteria in healthy adults.

Probiotics are live bacteria and yeasts, often added to yoghurt or taken as a supplement, that are promoted as helping stimulate the growth of "friendly bacteria" in the gut.

Supporters claim they can help treat a wide range of conditions, from eczema to irritable bowel syndrome (IBS), but there's little evidence to support many of these claims.

It has also been claimed that healthy people should take probiotics to improve their digestive health, a claim assessed in this latest review.

The review found seven trials, all with vastly different designs, methods and assessment of outcomes. As such, trial results could not be pooled in any meaningful statistical way.

Four of the trials found the probiotic had no different effect on gut bacteria from inactive placebo. Three of the trials reported some effect, but the overall quality of reporting for all trials was poor.

Given the limitations of the studies – including the variety of probiotics examined – it is not possible to conclude with certainty that all probiotics are ineffective.

Absence of good-quality evidence is not evidence of there being no effect. Better-designed studies may yet find some benefit from taking probiotics. 

Where did the story come from?

The study was carried out by researchers from the University of Copenhagen and was funded by the Novo Nordisk Foundation.

It was published in the peer-reviewed journal, Genome Medicine.

The UK media's reporting takes a very black and white attitude towards the review, concluding that probiotics "don't work" and are "a waste of time".

But they would benefit from considering the limitations of the small number of diverse trials included in this study. It would have been more accurate to say that based on the current evidence, we don't know whether they work or not.

It should also be noted that photos of yoghurt drinks – including Tesco own-brand – are misleading. Only one of the seven trials assessed a milk-based drink and we don't know what brand it was. Considering these were all non-UK studies, though, it is very unlikely to have been a UK supermarket brand.

What kind of research was this?

This systematic review aimed to gather the evidence from randomised controlled trials (RCTs) that have looked at the effect of probiotic supplements on gut bacteria.

As the researchers say, in recent years the composition of bacteria in the human gut has received considerable attention as a possible modifiable risk factor for various digestive and metabolic diseases.

This has led to a surge in the use of probiotic supplements to try to boost the health of the gut, through ways such as improving the intestinal lining and introducing more "friendly" bacteria to compete against the "bad" bacteria.

However, the effect of probiotic supplements – particularly in healthy individuals – is poorly understood.

This review therefore aimed to compile the evidence, looking at RCTs that have compared supplements with inactive placebo and used molecular approaches to measure gut bacteria. 

A systematic review is the best way of seeing if the evidence to date shows whether they are effective. But reviews are only as good as the studies they include.

Because of the vastly different designs of the various studies, the researchers were unable to perform a meta-analysis of the results.

What did the research involve?

The researchers searched three literature databases up to August 2015 to identify RCTs of any duration that:

• included healthy adults only
• compared probiotics with placebo
• assessed gut bacteria composition using specific molecular techniques and reported this as the main outcome

They excluded studies where other interventions were combined with supplement use, such as antibiotics or other medications.

Two reviewers separately assessed trials for eligibility, and carried out quality assessment and data extraction from the trials included.

Seven trials met eligibility criteria: two from Italy, two from Denmark, and one trial each from the US, Germany and Finland.

All were conducted in healthy adults aged 19 to 88 years, and the sample size of the individual studies ranged from 21 to 81.

Most supplements included Lactobacillus, in one trial combined with Bifidobacterium, and one trial used Bacillus. These were provided as capsules in four trials or in biscuits, drinks or sachets in one trial each. The length of the trials was typically one to two months.

The main source of potential bias in the studies was the lack of blinding of researchers assessing outcomes. 

What were the basic results?

The results of the seven studies are not pooled and are only reported study by study.

Essentially, none of the studies provided evidence that probiotics had a beneficial effect on gut bacteria.

The results were as follows:

• Four studies reported no difference in the diversity of, composition of, or stability of bacteria between probiotic and placebo groups.
• One study reported that the probiotic reversed the age-related increase in certain disease-causing bacteria (such as C. difficile and Campylobacter), but did not compare between groups.
• One study reported some difference in the diversity of bacteria, with increased abundance of certain bacteria (such as Proteobacteria) in the probiotic group.
• One study also reported some differences in the abundance of certain bacteria, but did not directly compare between groups.

How did the researchers interpret the results?

The researchers concluded that, "Overall, this systematic review demonstrates that there is no convincing evidence for consistent effects of probiotics on faecal microbiota composition in healthy adults."

Conclusion

This review finds no evidence that probiotic supplements have beneficial effects on the composition of gut bacteria in healthy adults.

The review has strengths in that it pre-specified exactly which trials would be eligible – that is, only RCTs in healthy adults, comparing probiotics with placebo, that assessed changes in gut bacteria levels as the main outcome.

This should aim to reduce diversity between the trials and try to find a definitive answer on the effect in a specific population.

However, despite this, the seven trials were still highly variable in their methods and design, such as the type of probiotic given and how gut bacteria were assessed.

This variability is demonstrated by the fact they are only reported narratively and the results could not be pooled to give an overall quantitative effect, as would be the case in a meta-analysis.

The trials also contained several quality limitations. In most, the researchers were not blinded to the assigned group, which may have biased their assessment of outcomes.

Only one of the seven trials had calculated beforehand how many participants they would need to recruit to detect whether the treatment had a significant effect. This is a notable limitation, given that all had sample sizes of less than 100.

Also, several of the trials had not statistically assessed, or not clearly reported, whether there was a difference between the probiotic and placebo groups. 

As the researchers say, future studies would benefit from clearly specifying the main outcome they're looking at, giving transparent results with statistical analyses, and clearly distinguishing within-group treatment effects – such as changes from study start to end – and between-group effects.

Further points to bear in mind:

• These trials only included healthy adults with no known diagnoses or conditions. This means the study can't tell us whether probiotics are effective in IBS or for "rebuilding" the gut bacteria in people who have had an illness. However, even though they were healthy adults, the trials included quite variable populations – for example, one was in elderly people, another specifically in postmenopausal women. We also do not know the effectiveness in children.
• There were only seven trials, and these used different probiotics containing different "friendly" bacteria, in different forms, from capsules to yoghurt drinks and biscuits. As such, there is not enough evidence to definitely conclude that all probiotics are ineffective, particularly given the limitations of the trials. It could be that certain bacteria in particular formulations could have different effects.
• None of the trials were from the UK, so the formulations used may differ from those on the UK market. 
• The trials were only of a couple of months' duration, so we don't know what longer-term use might have.
• The trials only looked at direct effects on gut bacteria level. We don't know whether taking the probiotic increased the person's sense of health and wellbeing, for example. If probiotics help some people in this way, that can only be a good thing – even if it is just a placebo effect.

Overall, the current state of the evidence does not demonstrate that probiotics have any effect on gut bacteria in healthy people.

Given the limitations of these studies, that is not to say that all probiotics definitely have no effect. Further high-quality research in their use is needed.  

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Are we sleepwalking into a 'global sleep crisis'?

Monday May 9 2016

The average bedtime for UK sleepers was 11.15pm

"We are facing a global sleep crisis because we don't go to bed early enough, say scientists," the Mail Online reports.

The warning comes from a study produced by a research team using a smartphone app (Entrain) to track sleep patterns from around the world.

The findings reveal that as people age, they tend to go to sleep earlier and wake later, and women tend to sleep more than men.

The researchers also found the timing of sunrise and sunset does influence sleep, but less than you might think.

Worldwide, there is a lot of variability in people's bedtime and the researchers believe this is down to social influences.

The researchers warn of a "global sleep crisis", but it is difficult to assess exactly what evidence this warning is based on.

The big stumbling block for this research is it can't provide us with any conclusive answers. It may be that factors such as using technical devices are disrupting our sleep, but we can't say anything about that based on this research.

Another drawback is that people chose to download this app. It could be that people with troubled sleep patterns would be more motivated to download the app than people with healthy sleep patterns.

Signs you may not be getting enough sleep include irritability and problems with concentration and memory. Persistent lack of sleep can make you more prone to accidents and chronic diseases.

Read more about why lack of sleep can be bad for your health.

Where did the story come from?

The study was carried out by researchers from the University of Michigan, and was funded by the Biomathematics Program at the Army Research Laboratory and the Human Frontier Science Program.

It was published in the peer-reviewed journal Science Advances on an open access basis, so it is free to read online or download as a PDF.

The Mail's headline, which says "we are facing a global sleep crisis", probably goes too far – the study provided no evidence to support the claims of an impending "sleep crisis". But, to be fair, this term was used in the study itself, but the researchers didn't elaborate on this.

What kind of research was this?

This cross-sectional study aimed to validate the use of mobile technology to collect information on sleep patterns worldwide, and explore the possible influences that social pressures have on sleep.

Sleep is known to be driven by our internal body clock. Naturally, sunrise and sunset would regulate this rhythm, but our modern lives are controlled by social factors, work obligations and artificial lighting, meaning we can't follow this natural rhythm.

As the researchers say, understanding the factors that control how much sleep we get is important as this can have a direct effect on human health.

In 2014 the researchers released a free app for iOS and Android devices – Entrain – that recommends optimal lighting schedules for adjusting to new time zones.

Users input data on their normal sleeping times, home time zone and typical lighting, sleep schedules and experience of jetlag.

In this study, the researchers analysed sleep habits from those who submitted data.   

What did the research involve?

In 2014, the first year of the app's release, 8,070 users submitted data.

The researchers explained that when the app is loaded, the opening screen asks users their normal wake time and bedtime to the nearest hour, home time zone, and typical amount of light exposure.

The options for typical light were:

• low indoor (200 lux)
• bright indoor (500 lux)
• low outdoor (1,000 lux)
• bright outdoor (10,000 lux)

For the purposes of this study, the researchers combined the indoor categories into a single group and did the same for the outdoor ones.

Users were also asked to give data on age, gender and travel frequency (from several times a week to less than once a year). They could also record data on travel dates and experiences of jet lag.

The main countries contributing data were the US (45%), Australia (9%) and Canada (5%). The UK, France, Spain, the Netherlands, Denmark and Germany jointly contributed 15% of the data, and China, Japan and Singapore made up 5%.

The researchers excluded "outlier" data that was far from the norm: for example, those who woke before 3am or after 11am, who went to bed before 7pm or after 3am, or who had less than 4 or more than 12 hours' sleep a night. This means most shift workers would have been excluded.

They also excluded those aged under 18 or above 85. This left 5,450 people for analysis. 

What were the basic results?

The adults analysed (majority male) represented a wide range of time zones, and more commonly reported indoor rather than outdoor light.

The researchers observed a relationship between age and sleep schedule, where in general increasing age was associated with less sleep and earlier waking times.

They found age has the strongest influence on the timing of midpoint of sleep, while gender had the strongest influence on duration of sleep, with women getting more sleep at nearly all ages.

Prior mathematical models suggested a later sunset and sunrise influence both bedtime and wake time, and the app data supported this. Sunrise after 6.30am and later sunset were both associated with later wake time and bedtime.

Later sunset was also associated with more sleep, particularly in the group who reported spending more time in outdoor light.

In general, women, older people and those with more outdoor light exposure seemed more sensitive to changes in sunset and sunrise than men, younger people and those with mostly indoor light exposure.

However, sunset timing had a weaker effect on bedtime than models may have predicted. The researchers considered that solar cues do influence sleep but may be ignored in the real world, particularly around bedtime.

The country the person resided in had an influence on their bedtime, suggesting that people are more responsive to social cues at night.

And sleep duration goes down as bed time becomes later. While average bedtime varied across countries, average wake time remained fairly consistent.

No results are reported for the influence of travel and reports of jet lag.

How did the researchers interpret the results?

The researchers noted that the trends they identified agree with previous large-scale surveys and laboratory studies, and validate the use of this mobile technology for assessing sleep.

They said that, "This work better defines and personalises 'normal' sleep, produces hypotheses for future testing in the laboratory, and suggests important ways to counteract the global sleep crisis." 

Conclusion

These findings show that the app works, and it is possible for people to input data on the timing and duration of their sleep for researchers to get a global picture of sleep patterns worldwide.

The researchers noticed a number of themes, including that age, gender and the amount of time we spend outdoors are factors that can influence the timing and duration of sleep.

Timing of sunrise and sunset do seem to have an influence on our sleep, but less than may be expected. Across countries worldwide there is most variability in the time we go to bed, and this directly influences our sleep duration.

The researchers also considered that social influences are causing us to go to bed later and ignore the natural influences of sunset.

However, this is the big stumbling block of this research – it can't provide us with any answers, and we can only speculate as to why this is the case.

It may be that factors such as late-night working, socialising or using technical devices are influencing our sleep, but we can't say anything about that based on this research.

Another limitation of the study is that excluding people with outlying sleep patterns – very late bed times or waking times – automatically excludes shift workers. This is often the group in which previous research has speculated disrupted sleep patterns could have an adverse effect on health.

There is also the potential for misclassification when people are asked to categorise their typical light exposure as indoor or outdoor. There is likely to be wide variation in the amount of natural daylight that people in these two broad categories are exposed to.

A final important limitation is that the population were self-selecting. People actively chose to download and use the application, meaning the study could be at risk of selection bias.

Arguably, people with sleep problems are more likely to download a sleep app than people without sleep problems, so the results may not be truly representative.

It is also worth noting that only a fraction of the data analysed comes from the UK, so the study can't give any great insight into this country's sleep patterns and influences.

Overall, the findings are undoubtedly of interest in furthering understanding of the world's sleep patterns. However, they raise more questions than answers on how our social and working lives are affecting our sleep and health.    

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Study finds no link between mobile phones and brain cancer

Monday May 9 2016

Around 4.7 billion people own a mobile phone

"Mobile phones don't increase the risk of brain cancer, 30-year study concludes," the Mail Online reports.

The Australian study found the massive increase in mobile phone use over the past 30 years was not matched by a similar rise in brain cancer cases.

The first official mobile phone call in Oz took place in 1987 by the then Minister of Communication, Michael Duffy. Now, mobile phone ownership rates are estimated to be around 94%.

Despite the explosion in Australian mobile phone ownership, the researchers found no corresponding spike in brain cancer rates. They therefore concluded there was no evidence that mobile phones cause brain cancer.

But the researchers only had the number of Australians with mobile phone contracts to play with – they didn't have any individual data, for example, with information about how often or for how long people had their phones to their heads or, increasingly in the smartphone era, held over their faces.

The study tells us that at a population level, it's unlikely mobile phone ownership is responsible for any moderate or larger increase in brain cancer in Australia. But it doesn't tell us about individual risk patterns.

Despite this uncertainty, when it comes to other risk factors for cancer, such as smoking, poor diet, drinking too much alcohol and lack of exercise, mobile phone ownership is probably not a significant risk to your health.

If you are concerned, read more about the potential risks of mobile phone use.

Where did the story come from?

The study was carried out by researchers from the University of Sydney and the University of New South Wales, Australia. No funding source was mentioned.

It was published in the peer-reviewed journal, Cancer Epidemiology.

The Mail Online coverage was accurate and contains a link to an article by the lead author, which may be of interest to those wanting more information about the background to the study and its possible implications.

What kind of research was this?

This ecological study set out to look for a link between mobile phone ownership and brain cancer incidence since the first mobile phone call in Australia in 1987.

Since the 1980s, mobile phone use has rocketed in most countries, including Australia, where more than 90% of the adult population use them today.

But mobile phones have been dogged by consistent and high-profile concerns that the electromagnetic radiation they give off might cause or contribute to cancer.

The researchers reference several reports showing an alleged link between mobile phone radiation and cancer, but say they had problems with the methods used in these studies, which meant the results were inconsistent and hard to replicate, and so may be wrong.

In an attempt to clear up the controversy, they set out to do a large, long-term study assessing the alleged link, bypassing many of the methodological flaws of previous research.

This sort of study is the most appropriate type to uncover any link between mobile phone ownership and cancer at a country level.

But as it is an ecological study, we need to resist the natural temptation to apply the country-level findings to individuals. We are dealing with averages of large groups, not individual cases.

What did the research involve?

All cases of cancer are recorded in Australia and have been for many decades. The percentage of Australians with mobile phone accounts was obtained from large mobile phone companies and governing bodies.

Putting these two pieces together, the researchers had mobile phone accounts dating between 1987 and 2014, and brain cancer diagnoses of 19,858 male and 14,222 females between 1982 and 2012. 

Their analysis looked at whether the rise in mobile phone ownership was linked to a rise in new cases of brain cancer, and they did this separately for different age groups and genders.

The researchers then probed the alleged link in more detail. Assuming a 10-year lag between phone radiation exposure and resulting cancer, they calculated the number of cancer cases they would expect to see if phone radiation caused cancer in a 20-year period, using the best estimates of risk increase from recent studies.

Their assumption was that mobile phones raised the risk of brain cancer 1.5 times for "ever-users" – those who'd used a mobile phone at any point in their lives – and 2.5 times for "heavy users", defined as more than 896 hours of total life use, which represented around 19% of Australians. These risk estimates were informed by previous research.

Using these assumptions, they were able to calculate an expected number of brain cancer cases if mobile phones caused brain cancer and compare it with the number of cases actually observed.

What were the basic results?

Mobile phone use in Australia rose from 0% in 1987 to 94% in 2014. Over a similar time period, 19,858 males and 14,222 females aged 20 to 84 were diagnosed with brain cancer from 1982 to 2012.

Age-adjusted brain cancer incidence rates over this time rose slightly in men but not at all in women. The rise in men was not attributed to mobile phone use.

Assuming mobile phones caused brain cancer, the researchers expected to see much higher rates of cancer than they did.

For example, the actual rate of brain cancer in men was 8.7 cases per 100,000 men, which should have been around 11.7 per 100,000 if the causal theory was true.

Combining men and women of all ages, they expected around 1,867 cases of brain cancer in 2012 if mobile phones were part of the cause (ever-users), but found significantly less: 1,434. The difference was even larger for heavy users: 2,038 expected compared with 1,434 actually observed.

One age group, 70 to 84 years, did show up as having similar expected and observed cases, but the rise in cases started in 1982, before the introduction of mobile phones, leading the researchers to conclude it couldn't be caused by mobiles. 

They thought it was probably the result of more access to better cancer diagnosis over time – picking up more cancer cases than in the past – leading to higher rates of cancer overall.

How did the researchers interpret the results?

The researchers concluded that: "After nearly 30 years of mobile phone use in Australia among millions of people, there is no evidence of any rise in any age group that could be plausibly attributed to mobile phones."

Conclusion

This ecological study found an explosion in Australian mobile phone ownership since the 1980s coincided with relatively little change in brain cancer rates, suggesting mobile phone ownership is unlikely to cause brain cancer.

This conclusion is based on assuming there would be a 10-year lag between mobile phone use and cancer, and 1.5 and 2.5 times risk increases due to mobile phone use. Using different assumptions may lead to different conclusions.

The study has many strengths, including its large size, comprehensive information on brain cancer rates over many decades, and research-based assumptions when modelling the expected number of cancer cases – assuming mobile phones do raise the risk of cancer.

What might be less obvious is that the study was more about mobile phone ownership rather than use. While you'd expect the two to be closely linked, it's important to spot the difference. 

The data the researchers had was about having a mobile phone contract – they didn't have individual patterns of use in terms of how often the phone was pressed up against users' heads emitting different strengths of radiation, for example.

As such, it's probably wise to use the term phone ownership, rather than phone use – used in the media – when talking about this study.

The study's conclusions are in line with other research quoted by this study, which showed no link between mobile phones and brain cancer.

The big problem with ecological studies are that they don't tell us about individual risk patterns, only about averages of large groups, in this case Australians. This is really useful for public health professionals who deal in population level issues, but less relevant for you and I.

For example, we can't infer from this study, however tempting, that mobile phone use doesn't contribute to brain cancer in some way, as the data simply isn't individualised or detailed enough to find out.

These caveats aside, it would be surprising, given the now massive ownership of mobile phones across the globe, if there was a strong cause and effect association, such as that between tobacco use and lung cancer.

If you are concerned, read more about the potential risks of mobile phone use. 

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Exercise benefits you - even in polluted city air

Friday May 6 2016

Exercise is worth it, despite pollution

"Why walking is good for you ... even in the smog. Health benefits of a stroll found to outweigh harm caused by chemicals and dust pumped out by traffic," says the Mail Online.

The report in question was carried out to see whether the harm caused by exposure to air pollution outweighs the benefit of doing exercise.

The study used computer modelling and found that the pollution level needed for the harms and benefits of exercise to become equal, the "tipping point", was only present in 1% of cities, according to the World Health Organization (WHO).

In an average city, physical exercise will remain beneficial for up to seven hours a day on a bicycle or walking for 16 hours. But in the most polluted cities, such as Delhi, this became as low as 30 minutes a day for cycling and 90 minutes of walking.

Although findings from these types of computer model studies have to be interpreted carefully, their findings can be quite accurate as long as the data used is accurate.

Keeping active can reduce your risk of illness such as heart disease, stroke and type 2 diabetes. This study suggests that in an urban environment you are unlikely to be putting your health at risk by exercising outdoors.

Where did the story come from?

The study was carried out by researchers from a number of institutions including the Centre for Diet and Activity research at the University of Cambridge and the Centre for Environmental Policy at Imperial College London.

Funding was provided by the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Medical Research Council, the National Institute for Health Research, and the Wellcome Trust.

The study was published in the peer-reviewed journal: Preventative Medicine.

The results of the study were presented accurately in the media.

What kind of research was this?

This was a health impact modelling study which assessed the risk-benefit balance between exposure to pollution through outdoor physical activity and the health benefits of exercise itself.

Previous work on the topic focused on high income countries with low pollution levels, but health risks are thought to rise with increased exposure to air pollution, this was investigated in the study.

Modelling studies are useful for investigating these scenarios, however as it is only a model it may never be true to life.

What did the research involve?

The researchers carried out computer simulations, using data from epidemiological studies and meta-analyses, to assess exposure to air pollution through physical activity and the associated health risks around the world.

Walking and cycling were considered in the simulations and the concentration of pollution established that was required to reach the "tipping point", where the risk from pollution and the health benefit from exercise are equal, and the "break-even" point, beyond which any time spent exercising would cause adverse health effects.

What were the basic results?

The researchers found that if cycling for 30 minutes, a pollution concentration (PM2.5) of 95 microgram/m3 (seen in less than 1% of cites according to the WHO Ambient Air Pollution Database) is required to meet the tipping point.

The breaking point is reached at a concentration of 160 microgram/m3.

For an average urban pollution concentration the tipping point would be reached after seven hours of cycling per day.

If walking for 30 minutes, the tipping and breaking points would be at a concentration above 200 microgram/m3, meaning in an average urban area, the tipping point would be reached after 16 hours of walking per day.

Highly polluted cities, such as Delhi, had low tipping and breaking points, these were 30 and 45 minutes of cycling per day.

Tipping points for the most polluted cities (44 microgram/m3 to 153 microgram/m3) varied between 30 and 120 minutes per day for cycling, and 90 minutes to 6 hours 15 minutes per day for walking.

How did the researchers interpret the results?

The researchers conclude: "The benefits from active travel generally outweigh health risks from air pollution and therefore should be further encouraged.

"When weighing long-term health benefits from PA [physical activity] against possible risks from increased exposure to air pollution, our calculations show that promoting cycling and walking is justified in the vast majority of settings, and only in a small number of cities with the highest PM2.5 concentration in the world cycling could lead to increase in risk."

Conclusion

This modelling study aimed to assess exposure to air pollution through physical activity and the associated health risks around the world.

The study found the background pollution level required to reach the tipping point is only present in less than 1% of cities, according to the WHO.

In an average city physical exercise will remain beneficial up to seven hours a day for cycling or 16 hours for walking.

In highly polluted areas this became as low as 30 minutes a day for cycling and 90 minutes of walking.

The main limitation of this study is that it is only a model and we do not know how true to life the findings are. But these studies can be quite accurate if representative data is used in the model.

The results will reassure those concerned about the effects of pollution on their health.

The study did not describe differences between children, adults and older adults or those with health conditions, as the tipping point may be different amongst these groups.

Keeping active can reduce your risk of illness such as heart disease, stroke and type 2 diabetes.

It is recommended that to stay healthy you should be active daily, this can be moderate activity for at least 150 minutes per week, 75 minutes of vigorous exercise or a mixture of both.

The findings of this study suggest that in an urban environment it is unlikely that you are putting your health at risk by exercising outdoors.

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from NHS Choices: Behind the headlines http://ift.tt/1q3PubM