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Brain health supplement market set for boost

The market for brain supplements is expected to grow by US $4,020.62m in the next four years – driven largely by an ageing global population.
Thriving urban communities and a rise in the number of retail sales outlets, are also expected to help push up the compound annual growth rate (CAGR) by 8.18% between now and 2027, according to the latest industry analysis from market research company, Technavio.
But it is the world’s geriatric population, who are more prone to age-related cognitive diseases, that are expected to be the main market driver in the coming years.
In 1965 there were 129 million over-65s across the globe. Today that figure has swelled to nearly 750 million. Population ageing is now the major global demographic trend, with the number of over 65s projected to hit 1.5 billion by 2050.
For the first time in history, in 2018 the number of persons aged 65 and over outnumbered children under five years of age globally.
Increased longevity has brought with it a host of health problems, however. The longer people live the more likely they are to develop chronic illnesses like cancer, dementia, cardiovascular disease, obesity and type 2 diabetes, and to suffer from serious mobility issues.
This has led to a boom in the health supplements market in general amongst this age group. A recent government study conducted in the US found that 80.2% of both men and women aged over 60 were taking health supplements.
Amongst the most popular were brain supplements, both prescribed and purchased, to help reduce the risk of cognitive decline. Research at Oxford has found that, in normal people, the level of vitamin B12 in the blood is related to the rate at which the brain shrinks.
The brain naturally shrinks as we age, but in the study people with low to normal levels of B12 showed more rapid wastage.
The Oxford study showed that those with mild cognitive impairment benefitted from a B vitamin mixture. It was vitamin B12 that turned out to be of most benefit.
The beneficial effects 0f B vitamins on the brain were enhanced in people with good omega-3 levels, the Oxford work found.
The Technavio analysis says it is the consumption of some of the most common brain supplements, including the B vitamins, omega-3 fatty acids, ginkgo biloba, bacopa monnieri, caffeine, and acetyl-L-carnitine, among others that are driving the growth of the segment.
North America is predicted to account for 41% of the market growth between now and 2027.
The report says: “ The growth of the regional market can be attributed to various factors including the rising awareness of brain health, rapid urbanisation, and the increased availability of brain health supplements through online channels. In addition, the presence of prominent vendors and the growing geriatric population drive the brain health supplements market in North America.”
Technavio acknowledges that the market is fragmented and recognises that the low penetration in developing countries is likely to hinder growth.
The report says: “The popularity of brain health supplements in developing countries is comparatively lower than in developed countries. The low purchasing power, lower awareness, and poor distribution channels have reduced the penetration of brain health supplements.
“However, the number of awareness programmes regarding these products is on the rise in developing countries. But the high price of these supplements restricts their adoption in such regions. All these factors reduce the growth potential of the market.”
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AI can predict Alzheimer’s with almost 93% accuracy, researchers say

Alzheimer’s AI can predict the disease with nearly 93 per cent accuracy using more than 800 brain scans, researchers say.
The system identified anatomical changes in the brain linked to the onset of the most common form of dementia, a condition that gradually damages memory and thinking.
The findings build on years of research suggesting AI could help spot early Alzheimer’s risk, predict disease and identify patients whose condition has not yet been diagnosed.
Benjamin Nephew, an assistant research professor at the Worcester Polytechnic Institute in Massachusetts, said: “Early diagnosis of Alzheimer’s disease can be difficult because symptoms can be mistaken for normal ageing.
“We found that machine-learning technologies, however, can analyse large amounts of data from scans to identify subtle changes and accurately predict Alzheimer’s disease and related cognitive states.”
The study used MRI scans, a type of detailed brain imaging, from 344 people aged 69 to 84.
The dataset included 281 scans showing normal mental function, 332 with mild cognitive impairment, an early stage of memory and thinking decline, and 202 with Alzheimer’s.
The scans covered 95 of the brain’s nearly 200 distinct regions and used an AI algorithm to predict patients’ health.
Being able to use AI to help diagnose Alzheimer’s earlier could give patients and doctors crucial time to prepare and potentially slow the progression of the disease.
The analysis showed that one of the top predictive factors was brain volume loss, or shrinkage, in the hippocampus, which helps form memories, the amygdala, which processes fear, and the entorhinal cortex, which helps provide a sense of time.
This pattern held across age and sex, with both men and women aged 69 to 76 showing volume loss in the right part of the hippocampus, suggesting it may be an important area for early diagnosis, the researchers noted.
However, the research also found that the way brain regions shrink differs by sex.
In females, volume loss occurred in the brain’s left middle temporal cortex, which is involved in language and visual perception. In males, it was mainly seen in the right entorhinal cortex
The researchers believe this could be linked to changes in sex hormones, including the loss of oestrogen in women and testosterone in men.
These conclusions could help improve methods of diagnosis and treatment going forward, Nephew said.
More than 7.2m Americans are living with Alzheimer’s, according to the Alzheimer’s Association.
More research is being done to reveal other impacting factors.
Nephew said: “The critical challenge in this research is to build a generalisable machine-learning model that captures the difference between healthy brains and brains from people with mild cognitive impairment or Alzheimer’s disease.”
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