Research and studies around the older population have greatly increased during the last 20 years. This is mainly due to the fact that the number of men and women who reach an older age is growing, thanks to the improvement of medical technology, which is resulting in a longer life expectancy (Shotton, Reference Shotton2003).
Already back in the 80s of 20th century in the USA data collected from various studies demonstrated that there was a large number of people who had reached an older age, and this had given birth to a debate regarding the social role and the quality of life they were living (White Riley and Riley, Reference White Riley and Riley1989). Changes in the structure of the families have brought to a different role of the elderly, who often in modern societies, end up living the last years of their lives in residential homes together with other peers, and away from their loved ones. This is especially true when the elderly have a diagnosis of dementia or Alzheimer’s disease since these conditions imply that they have to be looked after during all the day and sometimes, the conditions are so severe that they need a more specialized nursing assistance.
This is the reason why many researchers have pointed their attention mainly on the positive traits of the oldest old, in order to understand, which are the factors that can predict a healthier aging. In a research conducted in a small population of centenarians and nearly centenarians in Cilento, an area situated in the south of Italy, for example, it was found that they declared that what had allowed them to reach such a age, was, among other factors, the fact they still had a role in their families with which they were still living (Scelzo et al., Reference Scelzo2017). Almost all of them had no sign of dementia nor Alzheimer’s disease. Such considerations can also be found in studies conducted in the old population of Okinawa, an island in Japan, where although genes are considered as an important factor to predict longevity, it is the environment that has a great impact on the way people become old. Therefore diet, physical activity, smoking, social, and political role do play an important part in healthy aging (Suzuki et al, Reference Suzuki, Willcox and Willcox2016). We underlie the fact that research in this domain has to help understand how people can live longer in a healthy way, thus maintaining good cognitive abilities that allow to also have a good quality of life with satisfactory relationships with peers and younger people.
This is why we welcome works like the one written by Obhi et al., since we need to have instruments that can be used to evaluate memory performance and executive function. As a matter of fact through studies conducted via neuroimaging, it has been found that the executive function, located in the frontal lobes, is important for cognitive activities such as planning, maintenance, and the ability to make good judgments. In the past 30 years, the screening instrument mainly used has been the Mini-Mental State Exam, even though it does not evaluate all the cognitive areas considered important for a good quality of life such as language, memory, thought, executive function, attention, perception, judgment, the ability to live life with a purpose.
It is important to find good screening tools since the National Institute on Aging and the Alzheimer’s Association (NA-AA) predict an increase of AD to about 13.2 million by 2050 (Alzheimer’s Association, Centers for Disease Control and Prevention, 2013).
Knowing the signs that can predict the onset of dementia or AD can help people understand when it is time to ask for help, and on the other side could give an insight into measures that can be taken by the elderly to prevent the onset of neurological decline. In general although we cannot prevent the onset of AD, a lot can be done in order to treat the causes of cognitive decline that are reversible, that is, depression and delirium (Render et al., Reference Render2003). Other measures for prevention can be participating in programs that imply training memory.
The paper written by (Obhi et al., Reference Obhi2022) “Factor Analysis of the Cognitive Abilities Screening Instrument: Kuakini Honolulu-Asia Aging Study” represents an important step toward the integration of the tools that are necessary to assess the cognitive abilities of the older population.
This study deals particularly with the fact that till now, the Cognitive Abilities Screening Instrument (CASI) had been developed just using face validity, whereas it is pointed out that it should undergo a more profound evaluation using a factor analysis. With this in mind, Obhi et al. have particularly addressed their attention to two parameters, the crystallized and the fluid abilities in the older population, and have attempted to also test the one-factor analysis to determine which model could be more relevant for the findings.
The analysis was conducted using data coming from the subjects who participated in the Kuakini Honolulu-Asia Aging Study in 1991 (Kuakini Health System, Kuakini Honolulu Heart Program, 2018).
As Obhi highlights in his paper “the CASI assesses nine cognitive domains including long-term memory, orientation, visual construction, judgment/abstraction, language, short-term memory, attention, mental manipulation/concentration and list-generating fluency” and they hypothesize that factors of crystallized and fluid abilities would be reflected by the CASI factor structure.
Crystallized abilities refer to those life skills that are influenced by the culture and are maintained in older adulthood, whereas fluid abilities comprise all the basic processing of sensory information and visual memory (Baltes, Reference Baltes1993, Lee et al., Reference Lee, Chol and Gray2007) and tend to decline later in life (Hartshorne and Germine, Reference Hartshorne and Germine2015).
Research tends to suggest that fluid abilities can decline about 10 years before the onset of dementia while crystallized abilities tend to decrease approximately 5 years before a dementia diagnosis (Thorvaldsson et al., Reference Thorvaldsson2011).
The implication that changes in those abilities can predict that the onset of dementia is also supported by neuroimaging studies with significant changes in the cortical area, which diminishes when a decline in the crystallized and in the fluid abilities has been evaluated. At the same time, changes implying an expansion of the regions linked to cognitive abilities were observed when there was a greater performance in fluid abilities (Human Connectome Project).
Thus, the objective of Obhi et al.’s study was to “develop and test a parsimonious conceptualization of the CASI rooted in cognitive aging literature with factors representing crystallized and fluid abilities” and in particular, five domains within the crystallized category and four in the fluid category were identified. In the first category, we can find long-term memory, orientation, visual construction, judgment/abstraction, and language; the second category comprises short-term memory, attention, mental manipulation/concentration, and list-generating fluency.
The authors found that the proposed two-factor structure of crystallized and fluid abilities fit the data well and that there was a good correlation.
Particularly interesting is the finding that the language abilities domain measure and the mental manipulation/concentration domain measures had the highest loadings for the crystallized factor and fluid factor, respectively. The results are in line with prior research in which it was found that older adults tend to perform less on cognitive tasks reflective of fluid abilities (Murman, Reference Murman2015) and a little bit better on measures of crystallized abilities (Glisky, Reference Glisky2007).
Attention has to be particularly put on the fact that fluid performance was significantly and negatively associated with future dementia diagnosis. This is very important since this information can be used in order to help older people by organizing activities in which they can exercise short memory, attention, concentration, and list-generating fluency.
The current study shows us that the proposed two-factor analysis allows us to study and obtain details on underlying cognitive processes that can be of interest for investigators and clinicians especially, thus having a real-life applicability.
This study creates a good fundamental criterion to conduct future studies in which the two-factor model can be used to investigate how crystallized and fluid abilities change over time by conducting longitudinal studies, and also considering different ethnic populations and ages.
Furthermore, it urges societal and political agencies to consider investing in programs for people who are getting old and especially for those who are not living in a family context, thus not having any role in their lives and experiencing a lack of stimuli that can help the cognitive abilities to stay healthy. This is of utmost importance since it could really help to prevent dementia for many women and men who deserve to live a better quality life.
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Research and studies around the older population have greatly increased during the last 20 years. This is mainly due to the fact that the number of men and women who reach an older age is growing, thanks to the improvement of medical technology, which is resulting in a longer life expectancy (Shotton, Reference Shotton2003).
Already back in the 80s of 20th century in the USA data collected from various studies demonstrated that there was a large number of people who had reached an older age, and this had given birth to a debate regarding the social role and the quality of life they were living (White Riley and Riley, Reference White Riley and Riley1989). Changes in the structure of the families have brought to a different role of the elderly, who often in modern societies, end up living the last years of their lives in residential homes together with other peers, and away from their loved ones. This is especially true when the elderly have a diagnosis of dementia or Alzheimer’s disease since these conditions imply that they have to be looked after during all the day and sometimes, the conditions are so severe that they need a more specialized nursing assistance.
This is the reason why many researchers have pointed their attention mainly on the positive traits of the oldest old, in order to understand, which are the factors that can predict a healthier aging. In a research conducted in a small population of centenarians and nearly centenarians in Cilento, an area situated in the south of Italy, for example, it was found that they declared that what had allowed them to reach such a age, was, among other factors, the fact they still had a role in their families with which they were still living (Scelzo et al., Reference Scelzo2017). Almost all of them had no sign of dementia nor Alzheimer’s disease. Such considerations can also be found in studies conducted in the old population of Okinawa, an island in Japan, where although genes are considered as an important factor to predict longevity, it is the environment that has a great impact on the way people become old. Therefore diet, physical activity, smoking, social, and political role do play an important part in healthy aging (Suzuki et al, Reference Suzuki, Willcox and Willcox2016). We underlie the fact that research in this domain has to help understand how people can live longer in a healthy way, thus maintaining good cognitive abilities that allow to also have a good quality of life with satisfactory relationships with peers and younger people.
This is why we welcome works like the one written by Obhi et al., since we need to have instruments that can be used to evaluate memory performance and executive function. As a matter of fact through studies conducted via neuroimaging, it has been found that the executive function, located in the frontal lobes, is important for cognitive activities such as planning, maintenance, and the ability to make good judgments. In the past 30 years, the screening instrument mainly used has been the Mini-Mental State Exam, even though it does not evaluate all the cognitive areas considered important for a good quality of life such as language, memory, thought, executive function, attention, perception, judgment, the ability to live life with a purpose.
It is important to find good screening tools since the National Institute on Aging and the Alzheimer’s Association (NA-AA) predict an increase of AD to about 13.2 million by 2050 (Alzheimer’s Association, Centers for Disease Control and Prevention, 2013).
Knowing the signs that can predict the onset of dementia or AD can help people understand when it is time to ask for help, and on the other side could give an insight into measures that can be taken by the elderly to prevent the onset of neurological decline. In general although we cannot prevent the onset of AD, a lot can be done in order to treat the causes of cognitive decline that are reversible, that is, depression and delirium (Render et al., Reference Render2003). Other measures for prevention can be participating in programs that imply training memory.
The paper written by (Obhi et al., Reference Obhi2022) “Factor Analysis of the Cognitive Abilities Screening Instrument: Kuakini Honolulu-Asia Aging Study” represents an important step toward the integration of the tools that are necessary to assess the cognitive abilities of the older population.
This study deals particularly with the fact that till now, the Cognitive Abilities Screening Instrument (CASI) had been developed just using face validity, whereas it is pointed out that it should undergo a more profound evaluation using a factor analysis. With this in mind, Obhi et al. have particularly addressed their attention to two parameters, the crystallized and the fluid abilities in the older population, and have attempted to also test the one-factor analysis to determine which model could be more relevant for the findings.
The analysis was conducted using data coming from the subjects who participated in the Kuakini Honolulu-Asia Aging Study in 1991 (Kuakini Health System, Kuakini Honolulu Heart Program, 2018).
As Obhi highlights in his paper “the CASI assesses nine cognitive domains including long-term memory, orientation, visual construction, judgment/abstraction, language, short-term memory, attention, mental manipulation/concentration and list-generating fluency” and they hypothesize that factors of crystallized and fluid abilities would be reflected by the CASI factor structure.
Crystallized abilities refer to those life skills that are influenced by the culture and are maintained in older adulthood, whereas fluid abilities comprise all the basic processing of sensory information and visual memory (Baltes, Reference Baltes1993, Lee et al., Reference Lee, Chol and Gray2007) and tend to decline later in life (Hartshorne and Germine, Reference Hartshorne and Germine2015).
Research tends to suggest that fluid abilities can decline about 10 years before the onset of dementia while crystallized abilities tend to decrease approximately 5 years before a dementia diagnosis (Thorvaldsson et al., Reference Thorvaldsson2011).
The implication that changes in those abilities can predict that the onset of dementia is also supported by neuroimaging studies with significant changes in the cortical area, which diminishes when a decline in the crystallized and in the fluid abilities has been evaluated. At the same time, changes implying an expansion of the regions linked to cognitive abilities were observed when there was a greater performance in fluid abilities (Human Connectome Project).
Thus, the objective of Obhi et al.’s study was to “develop and test a parsimonious conceptualization of the CASI rooted in cognitive aging literature with factors representing crystallized and fluid abilities” and in particular, five domains within the crystallized category and four in the fluid category were identified. In the first category, we can find long-term memory, orientation, visual construction, judgment/abstraction, and language; the second category comprises short-term memory, attention, mental manipulation/concentration, and list-generating fluency.
The authors found that the proposed two-factor structure of crystallized and fluid abilities fit the data well and that there was a good correlation.
Particularly interesting is the finding that the language abilities domain measure and the mental manipulation/concentration domain measures had the highest loadings for the crystallized factor and fluid factor, respectively. The results are in line with prior research in which it was found that older adults tend to perform less on cognitive tasks reflective of fluid abilities (Murman, Reference Murman2015) and a little bit better on measures of crystallized abilities (Glisky, Reference Glisky2007).
Attention has to be particularly put on the fact that fluid performance was significantly and negatively associated with future dementia diagnosis. This is very important since this information can be used in order to help older people by organizing activities in which they can exercise short memory, attention, concentration, and list-generating fluency.
The current study shows us that the proposed two-factor analysis allows us to study and obtain details on underlying cognitive processes that can be of interest for investigators and clinicians especially, thus having a real-life applicability.
This study creates a good fundamental criterion to conduct future studies in which the two-factor model can be used to investigate how crystallized and fluid abilities change over time by conducting longitudinal studies, and also considering different ethnic populations and ages.
Furthermore, it urges societal and political agencies to consider investing in programs for people who are getting old and especially for those who are not living in a family context, thus not having any role in their lives and experiencing a lack of stimuli that can help the cognitive abilities to stay healthy. This is of utmost importance since it could really help to prevent dementia for many women and men who deserve to live a better quality life.
Conflict of interest
None.
Acknowledgements
I would like to thank Dr Dilip V. Jeste of the University of California San Diego for giving me the opportunity of writing this contribution.