As Americans grow older, the concerns regarding dementia amongst the elderly become more prevalent. Presently, nearly six million Americans suffer from the most common form of dementia, which is Alzheimer’s. It is expected that 14 million individuals will be afflicted with the debilitating disease by the year 2050.
No effective treatments are available at this time so it has become extremely important to investigate the factors that contribute to dementia.
Researchers are looking to large sets of data in an attempt to find patterns that might provide information regarding risk factors for dementia. The Framingham Heart Study, which was initiated in 1948 and has observed three generations of subjects, is one popular source of data. The primary function of FHS is the observation of factors leading to cardiovascular abnormalities.
A team of research physicians from Boston University recently made use of the data collected by the FHS in hopes of identifying risk factors that are susceptible to change in order to facilitate the prevention of dementia.
The analysis made by the researchers at Boston University was the first to use an approach that makes use of machine learning to produce clear pictures of dementia risk factors. Machine learning takes advantage of advanced statistics which allow computer systems to “learn” from available data without programming. This allows computer systems to spot patterns in data without the interference of human thought.
The data that was examined by the researchers was collected during a four year period from 1979 to 1983. The study focused its attention, particularly on lifestyle and demographics. The Journal Of Alzheimer’s Disease published the results of the study.
Not so surprisingly, age was confirmed to be an important risk factor as it has long been known that the more advanced in years a person becomes, the more likely they are to suffer the effects of dementia. However, the study was able to identify other significant risk factors.
Other risk factors identified by the analysis was becoming widowed, a lower body mass index, and inadequate sleep during middle-aged years.
Researchers hope this information will prove useful to both physicians treating patients as well as the population at large. Ph.D. Rhonda Au, co-author of the study says that she, along with colleagues, had the desire to produce information that medical personnel, as well as laymen, could use with simplicity to identify risk factors that can possibly lead to the development of dementia in the future.