Further, Otago researcher Dr Graham Eyres said, the range of flavourings in e-cigarettes had never been characterised nor quantified.
"This is concerning because some of the volatile organic compounds generated during vaporisation may be directly harmful if inhaled at high concentrations or may degrade to form harmful compounds."
He cited the use of diacetyl, a flavouring responsible for the buttery characteristic of chardonnay.
More than 20 years ago, it was linked to causing an incurable lung disease in popcorn factory workers who were breathing in large amounts of the compound over hot vats of oil while making flavoured popcorn.
Recent international research has shown that 74 per cent of commercial liquids in e-cigarettes contained diacetyl, with more than 40 per cent at concentrations higher than the recommended safety limits.
Yet the proportion of New Zealand e-cigarettes that contain diacetyl is unknown.
Eyres said his new study, funded by the Health Research Council (HRC) among 15 Explorer Grants, would redesign methods used in food science to better understand what compounds are found in the flavours, and how they're distributed in different-sized aerosol droplets.
"Armed with this knowledge, we can then work with toxicologists and health professionals to determine what the level of risk is from these compounds and hopefully provide regulators with the evidence they need to develop specifications and standards on e-cigarettes."
Worldwide sales of e-cigarettes have boomed around the globe over the past decade, and today an estimated three in 100 Kiwis use them at least once a day.
In 2019, more than a third of school students reported having tried an e-cigarette - and 12 per cent reported to be regular users.
The Ministry of Health's Vaping Facts website advises e-cigarettes are less harmful than smoking - but points out they haven't been around long enough for the long-term effects to be known.
HRC chief executive Professor Sunny Collings said the new research would provide some fundamental tools and data to help ensure that e-cigarettes didn't become yet another cause of harm.
"Smoking has a huge impact on public health and Māori health outcomes with half a million New Zealand adults smoking daily – 31 per cent of whom are Māori – and more than 5000 fatalities each year as a result," she said.
"E-cigarettes may have a part to play in achieving a smoke-free Aotearoa by providing an alternative to smoking cigarettes, however, we need to be able to effectively evaluate and monitor the safety of e-cigarettes and other vaping devices to ensure any long-term health effects on New Zealanders are minimised."
The new study comes after the University of Auckland's Dr Kelly Burrowes recently launched the most advanced study of its kind in the world, using human trials and state-of-the-art 3D computer models to get a precise look at what vaping does to our lungs.
A brain 'bio-marker' for ADHD
Meanwhile, another major project just funded by the HRC will examine more than 10,000 brain scans to identify the key brain processes underlying Attention Deficit Hyperactivity Disorder (ADHD).
The study, headed by University of Otago psychology lecturer Dr Narun Pornpattananangkul, could lead to a reliable "biomarker" to detect cognitive differences linked to the neurodevelopmental disorder.
Around 5 per cent of New Zealand children have ADHD, which can affect educational and employment attainment later in life, and it's also the most frequent diagnosis given to Māori children at mental health services.
Yet, currently, there are no reliable biomarkers for the cognitive differences associated with ADHD, making it difficult to detect the disorder early, as well as to assess treatment effectiveness and progress.
Pornpattananangkul plans to address that by building a neuroimaging model capable of predicting ADHD-related cognitive deficits in children, by looking at detailed MRI brain scans.
"What we call 'ADHD' currently is what clinicians can observe from the child," he said.
Over the next three years, his team hoped to capture the characteristics of the disorder, as a whole, from a biological perspective.
"In the long run, having highly reliable and predictive biomarkers for cognitive differences in ADHD can be a game-changer."
His team will be using a large dataset from more than 10,000 children from the United States, both with and without ADHD.
This dataset included brain images of various types, reflecting children's brain activity, connectivity and anatomy, as well as children's cognitive abilities based on various tasks.
His team will first examine the cognitive differences that occur in children diagnosed with ADHD.
They'll then apply specially designed machine-learning algorithms to accurately match up the brain images in the dataset with these cognitive differences.
This will result in a brain-based "predictive score" for each child in the dataset, reflecting their risk of developing ADHD-related cognitive deficits.
This brain-based predictive approach will then be tested for its applicability to New Zealand children who have been formally diagnosed with ADHD.
Functional and structural MRI scans of participants in Dunedin will be taken, and the resulting scores matched against each child's cognitive differences.
"The availability of such big data along with modern computation techniques, such as machine-learning, are the most exciting advances in psychiatry of our time, and will help generate a novel platform for neuroimaging and psychiatry."
In future, one of the benefits of a reliable biomarker would be in testing the efficacy of novel treatments that target cognitive functions.
"Our biomarker will help researchers see if treatments have an effect in cognitive areas of the brain."
In the longer-term, clinicians in New Zealand and elsewhere might be able to use the biomarker to aid in diagnosis, early detection, and management of ADHD.
"In the mental health world, people do not usually use neuroimaging as a predictive tool," he added.
"We're going to start this trend, and it's only made possible by the recent availability of large-scale brain data and by the advances in machine learning.
"It's still at an early stage, but I can say I see a bright future ahead of us."
