Mental decline inevitable with age

Mental (or cognitive) abilities improve throughout childhood and adolescence as the brain continues to develop (see Smith, Cowie & Blades, 2003). However, the brain is fully developed by around the third decade of human life (Toga, Thompson & Sowell, 2006). Ageing, and particularly old age, is associated with the stereotype of decreased mental performance and this decline is often viewed as inevitable (Park, 2000). The current essay will examine the inevitability of mental decline with ageing. The current essay will begin by examining the evidence that suggests mental decline is an inevitable consequence of ageing, before examining evidence suggesting that the neural changes associated with age-related mental decline may be avoidable, therefore suggesting mental decline need not be inevitable. The latter part of the essay will examine whether pathological ageing and the associated mental decline is inevitable, using Alzheimer’s disease (AD) as an example.

Crystallized intelligence refers to “the sum of acquired knowledge and experience” (Rolfus & Ackerman, 1996, p.175), whilst fluid intelligence refers to information-processing and reasoning abilities (Chamorro-Premuzic & Furnham, 2004). Several researchers have found evidence to suggest that fluid intelligence declines progressively with ageing, whilst crystallized intelligence remains stable across the lifespan (Bugg, Zook, DeLosh, Davalos & Davis, 2006; Horn & Catell, 1967; Park et al., 1996; Wang & Kaufman, 1993). For example, Wang and Kaufman (1993) used a cross-sectional design to study 500 individuals aged 20-90, whose crystallized intelligence was tested via a vocabulary test, and whose fluid intelligence was tested via a matrix reasoning task. Wang and Kaufman found that fluid intelligence peaked early in life and then declined steadily with ageing, whilst crystallized intelligence remained relatively stable across the lifespan. Similarly, Park et al. (1996) used a cross-sectional design to investigate cognitive decline in participants aged 20-90. Park et al. found age-related declines in working memory, long-term memory, and processing speed, but not in word knowledge. Park et al. suggested that these results reflected the fragile nature of fluid intelligence with ageing, but the relative stability of crystallized intelligence. The results of these studies, however, have all relied on the use of a cross-sectional design, whereby different cohorts (i.e. people born at different times) are measured at the same time (Schaie, 1965). Due to the relative efficiency of the cross-sectional design it has dominated the research on age-related mental decline (Hofer & Sliwinski, 2006). However, the cross-sectional design is confounded by cohort effects, such as education, environment and culture. As these variables all change over time, cross-sectional measures of age-related decline may reflect differences between age groups as opposed to changes within individuals due to ageing (Schaie, 1965, 1983). Although some studies attempt to control for education as a cohort effect (e.g. Wang & Kaufman, 1993) it should be recognised that a multitude of changes can occur with time, therefore confounding cross-sectional measures of age-related mental decline. For example, Schoenthaler and Bier (1999) found that poor diet habits during childhood could lead to impaired intelligence. Therefore the older adults in Wang and Kaufman’s (1993) study would have been children during the periods of World War One and Two, and rationing may have led to poor nutritional intake during childhood. In comparison the adults aged 20 would have grown up in periods where nutritional intake was much better and this could therefore have confounded their measures of fluid intelligence changes with ageing.

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An alternative method is the longitudinal design, which involves measuring the same individuals repeatedly as they age (Schaie, 1965). This type of design is much rarer in the research on age-related mental decline as it is time consuming and associated with high-drop out rates (Schaie & Strother, 1968). There are also difficulties in the study of normal ageing as longitudinal studies may inadvertently lead to the inclusion of individuals developing dementia (Hedden & Gabrieli, 2004), and the presence of “elite survivors” who may be more resilient to decline (Rabbit, Diggle, Smith, Holland & Mc Innes, 2001, p.532). Another difficulty with the longitudinal design in the measure of age-related mental decline comes from practice effects. Rabbitt et al. (2001) highlighted that practice effects were rarely acknowledged in research on age-related cognitive changes, and proposed that practice effects could mask actual age-related declines in cognition. However, Rabbitt et al. (2001) proposed a random effects model which dissociates age-related declines from practice effects. Using this model, Rabbitt et al. examined age-related changes on the AH4(1) intelligence test, which is designed to measure fluid intelligence, in 5,911 participants. When practice effects were controlled for, Rabbitt et al. (2001) found relatively small declines in fluid intelligence between 49 and 70 years of age, but more marked declines after the age of 70. Schaie (1996, as cited in Hedden & Gabrieli, 2004, p.88) reported similar findings from the large scale Seattle Longitudinal Study, with fluid intelligence declining after the age of 55, but appearing relatively stable up until this age. Hertzog and Schaie (1988) suggested that intellectual abilities remained stable throughout middle-age and declined after the age of 60. Their study suggested that differences between cohorts were much greater than differences within individuals, indicating that cohort effects may account for the steady age-related decline in fluid intelligence found with the cross-sectional design. The inconsistency between cross-sectional and longitudinal designs in terms of the onset of declines in fluid intelligence is an area in need of more extensive research, and increased use of the longitudinal design may elucidate whether mental decline is progressive with ageing, or begins in old age. However, both longitudinal and cross-sectional studies have found that with ageing, at some point, there is a decline in mental functions.

The results of the studies discussed so far have suggested that there is an age-related decline in fluid intelligence, but it is important to realise that some cognitive functions appear to be stable against ageing. Hedden and Gabrieli (2004) highlighted that studies generally show age-related declines in fluid intelligence and processing speed, but not in implicit memory (as well as autobiographical and short-term memory) and emotional processing. Hudson (2008) supported this finding in a study of implicit and explicit memory performance in young (19-39 years old), middle-aged (40-59 years old) and older adults (60-78 years old). Hudson found a significant decrease in explicit memory performance across all the age groups studied, whilst implicit memory performance did not differ significantly between any of the groups, supporting the findings of several other studies (e.g. Jennings & Jacoby, 1993; Titov & Knight, 1997). This evidence suggests that there is a gradual decline in explicit memory, but not implicit memory over the lifetime. Support for the age-related resilience of emotional processing came from Happe, Winner and Brownell (1998) who found that performance on theory of mind tasks remained stable, and on occasion even improved, as age increased. The results of this study, alongside the results of the studies already discussed that show crystallized intelligence remaining or improving with ageing, may elucidate the reasoning behind the stereotype that older people possess wisdom (Park, 2000); older adults may have more knowledge and experience to draw upon. In summary so far, the research has suggested that a global decline in mental functions is not inevitable with ageing, but that specific declines in fluid intelligence do occur with normal ageing.

The decline in processing speed across the lifespan is one finding that has consistently been shown in both longitudinal and cross-sectional studies (see Hedden & Gabrieli, 2004). This led to the development of the Processing-Speed Theory (PST; Salthouse, 1996), which suggested that the mental decline in older adults was caused by a limited time mechanism, whereby earlier processes take longer to complete leaving less time for later processes, and a simultaneity mechanism, whereby slower processing means a lack of information being available to other forms of processing. However, although this theory was proposed to account for older adults’ worse performance on tests of fluid intelligence and accounts for the mechanisms behind the trend of slower processing found with increasing age, studies (e.g. Wang & Kaufman, 1993) have suggested that even when time limits are removed there is still a decline in mental functioning in older adults. These findings suggest that PST alone cannot account for age-related mental declines. An alternative theory involves executive functions and the frontal lobes. Executive functions include task switching, inhibition, and mediating dual-task performance (see Gazzaniga, Ivry & Mangun, 2009). Mittenberg, Seidenberg, O’leary and Digiulio (1989) found that executive functions were highly affected by age-related declines, and this has been supported by studies showing decreased performance on measures of executive function with advancing age (Baddeley, Baddeley, Bucks & Wilcock, 2001; Robbins et al., 1998). Executive functions have been localised to the frontal lobes of the brain (D’Esposito et al., 1995; Eslinger & Damasio, 1985; Goldman-Rakic, 1992), and age-related declines in executive functions have been explained as being caused by age-related changes to the frontal lobes. Salat et al. (2004) measured the thickness of the cerebral cortex in 106 healthy participants aged 18-93, using magnetic resonance imaging (MRI). Salat et al. found cortical thinning in several regions of the frontal lobes with advancing age. Additionally, studies have shown that cerebral blood flow (CBF) decreases with normal ageing, particularly within the frontal lobes (Ackerstaff, Keunen, van Pelt, Montauban van Swijndregt & Stijnen, 1990; Buijs et al., 1998; Hagstadius & Risberg, 1989; Martin, Friston, Colebatch & Frackowiak, 1991; Matthew, Wilson & Tant, 1986; Pantano et al., 1984; Scheel, Ruge, Petruch & Schoning, 2000; Shaw et al., 1984; although see Meltzer et al., 2000, for difficulties in measuring CBF). The Frontal-Executive Theory (FET) suggests that declines in executive functioning and processing speed are caused by these age-related changes in the frontal lobes. Schretlen et al. (2000) measured perceptual speed, executive ability and regional brain volumes (obtained through MRI) in 112 normal ageing participants aged 20-92. Using multiple regression equations, Schretlen et al. examined whether PST, FET or a combination of the two best accounted for age-related changes in fluid intelligence. Schretlen et al. found that the FET and PST complemented each other and suggested that the degradation of the frontal lobes, as well as the slowing of perceptual speed through the PST mechanisms, caused age-related declines in fluid intelligence, executive ability and processing speed. This complementary approach was also supported by Bugg et al. (2006). Therefore, research has suggested that mental decline occurs with ageing, and is associated with age-related changes to underlying neural structures.

The neural changes associated with mental decline in normal ageing, however, may not be inevitable. Clarkson-Smith and Hartley (1989) tested 124 older individuals, half of which participated in vigorous exercise and half of which did not. Clarkson-Smith and Hartley reported that the individuals who exercised showed significantly better performance on reasoning and working memory tasks, as well as showing improved reaction time performance, when compared to the non-exercising group. Shephard and Balady (1999) and DeSouza et al. (2000) highlighted that exercise has a positive effect on cardiovascular function, allowing higher oxygen intake and improving blood flow. In other words exercise improves CBF. Laurin, Verreault, Lindsay, MacPherson and Rockwood (2001) studied 9,008 individuals aged 65 or over and reported that higher levels of physical activity were associated with reduced risk of any form of cognitive decline. Additionally, Hawkins, Kramer and Capaldi (1992) reported that older adults who had engaged in exercise showed better dual-task performance than older adults not engaged in an exercise program. Dual-task performance is a key function of the central executive, and so this research suggests that exercise can help counter-act age-related declines in executive functioning, possibly by increasing CBF or oxygen intake (see Hall, Smith & Keele, 2001) to the frontal lobes. Additionally, Colcombe et al. (2003) found that exercise vastly reduced the loss of tissue density in the frontal, parietal and temporal cortices, helping reduce the mental decline associated with these areas. Therefore, the research suggests that age-related declines in the neural areas associated with executive functioning are not inevitable, and therefore age-related declines in executive functions may not be inevitable either.

Furthermore, several additional factors have been found that reduce the likelihood of general age-related mental decline in healthy individuals. Hultsch, Hertzog, Small and Dixon (1999) investigated 250 middle-aged and older adults, tested three times in six years, and found that participating in intellectually engaging activities provided a buffer against mental decline. Diet has also been implicated as important in reducing age-related mental decline in normal ageing individuals. Solfrizzi et al. (1999) analysed data from 278 non-demented elderly subjects, whose cognitive functions were measured via the Mini-Mental State Examination and several other neuropsychological tests. Solfrizzi et al. found an inverse relationship between the intake of monounsaturated fatty acids (MUFAs) and cognitive decline, and concluded that a high intake of MUFAs provided a buffer against normal age-related mental decline. Galli, Shukitt-Hale, Youdim and Joseph (2002) found that diets involving the increased intake of fruit and vegetables high in anti-oxidants led to the prevention, and in some cases reversal, of age-related declines in normal ageing individuals. Galli et al. concluded that a healthy diet was vital for maximum functioning in old age. Therefore evidence shows that age-related mental decline in executive and general mental functions, often relating to fluid intelligence, may not be inevitable, as several factors have been found that appear to prevent the mental decline and neural degeneration associated with normal ageing. However, if these preventative methods are not engaged in, some aspects of mental function appear to decline with ageing. Finally, it should be noted that Wilson, Beckett, Bienias, Evans and Bennet (2003) reported evidence, based on 122 participants who completed an average of 5.6 annual evaluations consisting of a battery of cognitive tests, that suggested that sharp declines in global mental functioning may be inevitable in normal ageing individuals in the last three to six years of life.

One important question in the research on age-related mental decline concerns the inevitability of dementia, a form of pathological ageing. Alzheimer’s disease (AD) is the most common form of dementia accounting for 60 per cent of all dementia cases (Alzheimer’s Research Trust, 2010). AD is associated with the presence of amyloid plaques between neurons, neurofibrillary tangles within neurons, and the degradation of the hippocampus, although its exact cause is unknown (Gazzaniga et al., 2009). AD degeneration appears to begin in the medial temporal lobes (MTLs), the neural area associated with explicit memory (see Corkin, Amaral, Gonzalez, Johnson & Hyman, 1997; Schacter, Alpert, Savage, Rauch & Albert, 1996; Scoville & Milner, 2000; Squire et al., 1992) therefore causing severe memory deficits, although later-stage AD is associated with more widespread cognitive and neural decline (see Buckner, 2004; Gazzaniga et al., 2009). The onset of AD has proved difficult to differentiate from the memory declines associated with normal ageing. Spaan, Raaijmakers and Jonker (2003) found that the use of clinical tests based around episodic memory meant that early-stage AD and normal ageing are often not distinguishable. Spaan et al. suggested that semantic knowledge and implicit memory are generally more greatly reduced in early-stage AD patients than normal ageing individuals, and that clinical tests need to examine semantic and implicit memory in order to identify early-stage AD. Hudson (2008) found explicit memory to be severely impaired and implicit memory to show some impairment in AD patients when compared to healthy age-matched participants. The use of the process dissociation procedure (Jacoby, 1991), an oppositional experimental method that derives uncontaminated estimates of implicit and explicit memory, may therefore provide a useful method for identifying early-stage AD. However, much further research using a larger population to establish reliability is needed. Additionally, Simic, Kostovic, Winblad and Bogdanovic (1997) highlighted that the neurofibrillary tangles, amyloid plaques and hippocampus degeneration associated with AD are found in the brains of normal ageing individuals, but are present to a greater extent in the brains of individuals with AD. This led to the suggestion that AD is a form of accelerated ageing, and that differences between normal ageing and AD are only quantitative (e.g. Selkoe, 1982). In other words AD is just an accelerated form of the neural changes that would occur in normal ageing given enough time.

Recent research has suggested that AD is, however, not quantitatively different to normal ageing but is associated with distinct degenerative processes (Simic et al., 1997). West et al. (1994) found distinctive neuron loss in the CA1 region of the hippocampus in participants diagnosed with probable AD, whilst normal ageing individuals showed little neuron loss within this area (see also Simic et al., 1997). Similarly, Gomez-Isla et al. (1996) found that the entorhinal cortex, which connects the neocortex and hippocampal formation, showed over 32% fewer neurons in those with AD compared to healthy controls. Importantly the number of neurons in the entorhinal cortex of normal ageing controls remained constant between the ages of 60 and 90, suggesting that the decline in neurons associated with AD was not due to accelerated ageing or accelerated neuron loss, but due to a qualitative difference caused by distinct pathological changes (see also Price et al., 2001). Additionally, Jobst et al. (1994) found an average yearly rate of MTL atrophy of 15.1% in those diagnosed with probable AD compared to just 1.5% in normal ageing controls. Jobst et al. concluded that that the MTLs were vulnerable to a catastrophic event and therefore AD was not “due simply to an acceleration of normal ageing, but, rather is the consequence of a true disease process” (p.829). The evidence, consequently, suggests that qualitatively different neural changes occur in normal and pathological ageing, and therefore pathological mental decline, in the case of AD, is not inevitable. Like in normal ageing, several preventative factors have been associated with reducing the likelihood of the onset of AD and the associated mental decline. Anti-oxidising measures increasing vitamin B12 levels (Clarke et al., 1998; McCaddon Regland, Hudson & Davies, 2002; Solfrizzi, Panza & Capurso, 2003), and engagement in cognitive tasks (Wilson et al., 2002) have been found to reduce the likelihood of AD developing, further supporting the notion that pathological ageing, of the AD type, is not inevitable.

The evidence presented suggests that global mental decline is not inevitable with normal ageing. However, declines appear to occur in specific mental functions, and these declines are likely caused by a combination of slower processing and neural changes in older individuals. Importantly, these declines appear not to be inevitable as preventative measures have been found that reduce the likelihood of mental decline occurring with normal ageing. However, it should be acknowledged that different individuals may respond differently to these preventative methods, or may be predisposed, through their genetics, to greater or lesser amounts of mental decline (see Hedden & Gabrieli, 2004). It should also be noted that some form of mental decline may be inevitable in the last few years of life. Additionally, AD related pathological ageing appears to be qualitatively different to normal ageing, and the discovery of preventative techniques that can reduce the likelihood of AD, suggest that pathological ageing and the associated mental decline, is not inevitable. Future research must examine whether normal age-related mental decline occurs continually throughout the lifespan or only occurs in old age, focusing particularly on the cognitive changes that occur between the ages of 30 and 60, as these age groups are rarely studied in favour of younger or older adults (Hedden & Gabrielie, 2004); further use of the longitudinal design, examining intra-individual differences, may prove useful here. Future research must also continue to examine, and make the public aware of, the factors that minimise the likelihood of both normal age-related mental decline and pathological ageing. In summary, the evidence suggests that mental decline is likely to occur with normal ageing, but that this decline may not be inevitable if preventative strategies are engaged in. Additionally AD related pathological ageing, and the associated mental decline, appears not to be inevitable.

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