The average education level of the 28 older adults was The average height was For all but 3 older adults we obtained a MOCA score Montreal Cognitive Assessment and they scored 26 or higher, which is considered normal. The young participants did not complete aerobic fitness testing. All young participants were currently enrolled as university students with the University of Birmingham. All participants gave informed consent and were monetarily compensated for participation.
All were non-bilingual native British English speakers with no speech or language disorders and no dyslexia. The research was conducted at the University of Birmingham. The evaluation consisted of a general health questionnaire, a resting lead electrocardiogram ECG assessment and a resting blood pressure measurement.
This information was then reviewed by a cardiologist MR. Furthermore, for 3 older adults who passed the screening protocol, exercise testing on the ergometer had to be terminated before a fitness score was obtained because the participants experienced knee pain. Two older adults choose to withdraw participation post-screening. As a result, fitness scores were obtained for 28 older adults. In the retained sample of 28 older adults who completed fitness testing, 4 older adults were taking anti-hypertension medication, 3 older adults were on cholesterol lowering medication, and 1 older adult was taking both types of medication.
Submaximal estimation of maximal aerobic power is a standard procedure for measurement of fitness in sedentary older adults and clinical populations. Scores therefore must be normed or standardized. Each participant received the 60 definitions in a random order. The sequence of events on each trial was as follows. However, sometimes we feel sure we know a word but are unable to think of it. If participants indicated they experienced a tip-of-the-tongue state, they were asked to provide three pieces of information about its sound structure in response to prompts on the screen which asked them to: 1 guess the initial letter or sound; 2 guess the final letter or sound, and 3 guess the number of syllables.
We analysed the data using mixed effects models, which are an extension of classical linear regression models. Mixed effects models are the most suitable models to analyse the present dataset because they can account for the fact that there are repeated observations for both items and participants. We modelled tip-of-the-tongue occurrence using mixed effects logistic regression 40 , 41 in R For a categorical outcome variable such as tip-of-the-tongue occurrence, a logistic regression is much more suited than an ANOVA to model the data In such instances, regression methods are thus preferred However, ordinary regression analysis ignores correlation of observations within clusters and treats within cluster observations the same as between cluster observations producing invalid standard errors of the fitted coefficients Any subsequent analysis based on these standard errors e.
The use of mixed effect models allows accounting for the fact that there are repeated observations for both items and participants 40 , 41 and therefore used frequently in psycholinguistic literature. In addition to modelling tip-of-the-tongue occurrence, we also fitted a model for phonological access scores. We calculated a phonological access score for each trial on which the participant reported a tip-of-the-tongue: 1 point for listing the correct initial sound, 1 point for the correct final sound and 1 point for the correct number of syllables resulting in a score between 0 and 3.
Phonological access scores were modelled using mixed effects linear regression 41 in R 42 , again to account for the fact that there are repeated observations for both items and participants. Continuous variables were centered. Group was deviation coded. We started with including a maximal random effect structure as justified by the design and in the case of non-convergence we simplified the random effects structure until convergence was reached.
The random effect associated with the smallest variance is dropped and this is done progressively until convergence is reached During the process of model comparison, we started with a model including all fixed effects and then simplified the model using model comparison for fixed effects in stepwise fashion until a model was reached with the lowest AIC value Akaike information criterion.
Main models are summarized in tables; coefficient estimates are included in the text only when a full summary is not included in the tables. Thus there is no direct evidence on which we could postulate a hypothesized effect size prior to conducting the present study. Rather than postulating a hypothesized effect size based on indirect evidence, we performed a power analysis simulation study which can be a basis for future work.
Indeed, any result of a power calculation depends entirely on the size of the hypothesized effect, for which it is impossible to obtain an accurate estimate until direct evidence from a first study is available. The current research may then serve as a benchmark for future studies.
We investigated the power of detecting a non-zero effect of aerobic fitness on the probability of experiencing a tip-of-the-tongue state by means of a simulation study under the statistical model describing the present data. As such, we can, based on informative evidence, investigate the Type II error which depends on both the effect size and the sample size. The simulation study allows us to generate data independent of the data described in the current work.
Moreover, simulation studies are an effective way of obtaining a power estimate for complex models 47 , 48 , 49 and the approach has been used in the field of psychology in recent years 50 , 51 , The results of our simulation will serve as in important indicator for postulating sample size in future studies. Further details are described in the results section.
Christensen, K. Ageing populations: the challenges ahead. The lancet , — Birmingham Policy Commission published online February Lovelace, E. Bulletin of the Psychonomic Society 28 , — Maylor, E. Age, blocking and the tip of the tongue state. British Journal of Psychology 81 , — Ossher, L. Everyday memory errors in older adults. Aging, Neuropsychology, and Cognition 20 , — Salthouse, T. Do age-related increases in tip-of-the-tongue experiences signify episodic memory impairments?
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Higher physical fitness levels are associated with less language decline in healthy ageing
Stroke 44 , — Voss, M. Bridging animal and human models of exercise-induced brain plasticity. Trends in cognitive sciences 17 , — Aerobic exercise training increases brain volume in aging humans. Human brain mapping 34 , — Menenti, L. The neuronal infrastructure of speaking. Shafto, M. Word retrieval failures in old age: the relationship between structure and function. Journal of Cognitive Neuroscience 22 , — On the tip-of-the-tongue: neural correlates of increased word-finding failures in normal aging.
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Cerebral blood flow and cerebrovascular reactivity at rest and during sub-maximal exercise: effect of age and week exercise training. People who start exercising increase their PF whereas people who quit exercising lose PF. Interestingly, the initial value of PF for later quitters is lower than for continuous athletes.
PF by age and sport activity. BMI is negatively associated with PF. A decrease of 0. However, a positive estimate of the interaction parameter between squared age and BMI shows that, in very high age groups, this relationship is reversed. Finally, significant random effects of the constant term and BMI and age signalize significant amounts of intrapersonal variance in these parameters, respectively, the initial value of fitness performance.
An average inactive participant aged 28 shows a HS score of 1. Age is the strongest predictor of HS with an increase of 0. Squared age was not a significant predictor indicating a linear age-related increase of the HS score. BMI is also a strong predictor of HS with an increase of 0. Exercising in general shows significant positive effects on maintaining a good HS.
However, a significant, negative associated interaction term between squared age and athlete shows that athletes also lose HS and even faster at high ages. Figure 3 shows the development of HS over the course of the observed lifespan for four different exercise groups. HS by age and sport activity. Besides moderating the effect of HA, the basic term of sex shows a slightly higher limitation-score for men. Contrary to PF, the constant term of the HS model has no significant random effect, indicating a more or less identical initial value between participants aged However, a significant random effect of age shows that the slope of HS differs within participants.
With increasing age, PF is decreasing and physical health limitations are increasing while SA is decreasing. These findings are consistent with numerous other studies [ 8 , 28 ] and indicate that physical health parameters as well as SA decline with increasing age. Comparable amounts of habitual activity showed significantly smaller benefits and WRA showed no relationship to PF and only a low, inconsistent association with HS. Besides sex and age, SA turned out to be the most meaningful predictor for PF.
Athletes possess a better PF than nonathletes in every age group and participants who started to exercise throughout the study gained, whereas participants who quitted exercise lost PF. This is in line with other studies about SA and PF [ 24 , 29 ]. The amount of reported SA also showed a positive relationship to PF.
The results confirm that, during every stage of life, SA is essential for keeping sufficient motor skills [ 30 , 31 ]. This may be due to the unsystematic character of HA and to its lower overall intensity. Few other studies did differentiate between HA and SA but those who did showed similar results. A recent study about aerobic fitness, exercise training, and HA showed that while exercise training enhances aerobic fitness, HA shows no meaningful relationship with fitness during youth [ 32 ]. The fact that WRA showed no positive effect on fitness has also been shown in previous studies.
Recent results from a Canadian workplace management program with participants showed that the level of physical activity at work is not related to cardiorespiratory fitness or anthropometrics and cardiometabolic risk profile [ 33 ]. Other studies reported even negative effects of WRA on health parameters. In this paper not presented analyses that differentiated fitness between motor performance abilities showed that WRA is negatively associated with flexibility, especially when people get older.
Participants who reported to exercising showed a significant better HS than inactive. However, compared to the findings for PF, exercising showed less impact on HS. Even though many other studies do not differentiate between SA and HA, there is consensus about an overall positive relationship between leisure time PA and health parameters [ 34 ]. Interestingly our data showed that, starting from a higher level, the loss of HS in elderly athletes was higher than in nonathletes.
This indicates that athletes cannot maintain their excellent HS for a lifetime and HS of athletes and nonathletes converges at higher ages. Further studies with high aged participants that investigate this finding are needed. In addition to the positive relationship between exercising in general and HS, no positive relationship between the amount of SA and HS was observed.
This is in line with a study from Dorn et al. The authors report a positive relationship between PA and mortality risk but only for nonobese men and women. This thesis is supported by the data from Arem et al.
This may be true for applied, supervised exercising but has to be reconsidered and further analyzed for daily life PA. In our study, WRA was negatively associated with HS in early and midadulthood but a significant positive associated interaction between squared age and WRA indicates that, at older ages, people who report high amounts of WRA show a better HS.
A recent Scandinavian study showed that moderate and unfit people with high occupational physical activity are at higher risk for cardiovascular and all-cause mortality [ 38 ]. These findings about WRA are contrary to the early findings of Morris in his London Transport Workers Study [ 39 ]; however recent studies focus on a broader range of work related activities and also physical intense activities at work are included.
Many studies report that unsystematic PA like HA is not sufficient to achieve health outcomes [ 32 ]. In our study a significant interaction between HA and sex indicates that especially men benefit from HA. This could be due to higher intensities and higher amounts of HA among men which lead to successfully reaching the threshold for significant health effects in late adulthood. Men showed higher levels of PF than women, but a significant interaction term between sex and age showed that these differences decline with increasing age.
Men showed a slightly worse HS compared to women. The influence of SES on HS is in line with other studies, showing a health benefit from higher SES [ 40 , 41 ] but there are also studies who lack finding a consistent pattern of association between SES and health outcomes [ 42 ]. Lower values for PA and PF for residents with lower SES have been reported in numerous studies with adults [ 40 ] as well as adolescents [ 43 , 44 ]. The reason for this finding may lay in the phenomenon of sarcopenia, a decline in muscle mass in the elderly, which is indicated by a loss of BMI in late adulthood [ 45 ].
Whereas in some individuals an increasing BMI due to an increase in muscle mass can go along with an increase in PF, in others, an increase in BMI due to body fat is negatively associated with PF. The main strengths of this study are the longitudinal data over a course of 18 years and the broadened view of PA, PF, and HS.
The average SA of about 10 MET-hours per week lies in the range of a representative German study that reports an average of Though, the relatively high values for SA and HA among participants who aged 61—80 indicate a bias towards more active longitudinal participants. Nonresponder analyses showed that the difference between responders and nonresponders in HS, PF, and PA on their average last examination is under ten percent.
We assume that the reason for a relatively low longitudinal bias is the distinct focus on health during the examination. We experienced that many unfit and relatively unhealthy participants remain in the sample because they use the opportunity of a detailed health check with an extensive talk to a practicing doctor. In this study we draw conclusions about daily life PA and fitness and health from an observational longitudinal study because we believe that there is a lack of knowledge about effects of daily life PA on fitness and health.
From cross lagged panel designs we know that the relationship between PA and health is bidirectional [ 46 ] and in order to unravel clear dose-response principles we need random controlled studies [ 24 ]. However the aim of this study was to sensitize for the high impact of the context and content of PA and therefore our target was not to express causal effects in first line. When methods of data collection are concerned the detailed assessment of PF and HS is a mentionable strength of this study.
However, using a questionnaire to assess PA, variables tend to have low validity and reliability [ 47 ]. In order to obtain comparable data with accelerometers, participants would have to wear an accelerometer over the course of a broad time span e. Defining time frames of different types of PA with the doubly labeled water method is even more striking and not feasible. This study shows that different types of daily life physical activity differ in a meaningful way in their effects on fitness and health when a large lapse of time is observed.
Whereas SA was positively associated with fitness and health with the exception of high amounts of SA at high BMI levels, comparable amounts of habitual activity showed only small benefits and WRA showed no or inconsistent effects. These findings show that the context and content, for example, adequate intensity, frequency, and execution, of PA are very important to utilize its benefits in daily life. The accelerated decline of HS in athletes as well as the high average of health limitations in sport quitters should be further examined.
This study was approved by the ethics committee of the Karlsruhe Institute for Technology.
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National Center for Biotechnology Information , U. Journal List Biomed Res Int v. Biomed Res Int. Published online Mar Steffen C. Author information Article notes Copyright and License information Disclaimer. Schmidt: ude. Received Jan 26; Accepted Mar Schmidt et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Introduction There is consensus that regular physical activity PA can improve physical fitness PF and health and assist in the prevention of disease [ 1 , 2 ]. Open in a separate window. Figure 1. Research Methods 2. Study Sample and Design The data was drawn during a community-based, longitudinal study in Germany [ 20 ] with four measurements in , , , and Table 1 Descriptive statistics of adult participants of the longitudinal study in Germany.
Measures 2. Physical Activity Weekly sports activity, habitual activity, and work related activity were assessed via questionnaire. Physical Fitness PF In total 13 motor performance tests were used to assess physical fitness [ 26 ].
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Physical Health Status HS Physical health status was assessed during a laborious health examination conducted by a practicing physician. Socioeconomic Status SES Based on methods for social structure analyses [ 27 ], the subjects were classified into four socioeconomic status categories using information about formal education and professional status. Results 3. Physical activity and health of youth.
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