Relationship between aging-related pulmonary function,cognition,motor function,and activities of daily living in older adults with dementia

Abstract

BACKGROUND:

The aging process is related to cerebrovascular dysfunction and physiological changes, such as reduced pulmonary function. This ultimately induces cognitive impairment or dementia.

OBJECTIVE:

This study aimed to determine the relationship between aging-related pulmonary function, cognition, motor function, and activities of daily living (ADLs) in older adults with dementia.

METHODS:

This cross-sectional study included 69 older adults diagnosed with dementia. Aging-related pulmonary function and cognition were measured using a hand-held spirometer and the Korean version of the Mini-Mental State Examination (MMSE-K), respectively. To assess motor function and ADLs, the Berg Balance Scale (BBS), 10-meter walk test (10-MWT), 6-minute walk test (6-MWT), and modified Barthel index (MBI) were used to measure balance, walking speed, physical functional capacity (or walking tolerance), and ADLs, respectively. All data were analyzed using the Pearson’s product correlation coefficient (r).

RESULTS:

Forced vital capacity (FVC) and forced expiratory volume in one second (FEV₁) as measures of aging-related pulmonary function correlated only with the 6-MWT (FVC: r = 0.483, p = 0.002; FEV₁: r = 0.512, p = 0.001). In cognitive function, MMSE-K was associated with BBS (r = 0.283, p = 0.022) and MBI (r = 0.454, p = 0.000). Additionally, there were significant correlations (r = 0.425–0.671, p = 0.000) between all motor function and ADLs measures in older adults with dementia.

CONCLUSIONS:

Our findings demonstrated that aging-pulmonary function was related to a lower physical functional capacity, and hence, suggested that the reduced pulmonary function were unable to walk for longer distance in older adults with dementia.

Keywords

Aging cognition dementia motor function pulmonary function

1 Introduction

Dementia continues to be a major public health concern for older adults. It is estimated that by 2050, the number of people with dementia will increase to 131.5 million worldwide (Prince et al., 2019). Dementia is a neurodegenerative cortical and subcortical dysfunction characterized by progressive and severe cognitive decline, motor deficits, and behavioral problems, resulting in a decline in activities of daily living (ADLs) (Alzheimer’s Association, 2019). The aging process may lead to cerebrovascular dysfunctions (Yang, Sun, Lu, Leak, & Zhang, 2017) and associated physiological changes, particularly reduced pulmonary function (Sharma & Goodwin, 2006). The aging-related pathophysiological processes of the cerebrovascular system include arterial stiffness (the expression of mechanosensitive genes leading to vascular remodeling, oxidative stress, and pro-atherogenic changes in the vascular wall) (Sharma & Goodwin, 2006; Ungvari, Kaley, De Cabo, Sonntag, & Csiszar, 2010), endothelial replicative senescence (inhibition of the proliferation of mitotically competent cells and secretion of multiple inflammatory cytokines in senescent cells) (Campisi, 2003), microvascular rarefaction (especially the hippocampus) (Riddle, Sonntag, & Lich-tenwalner, 2003), narrowing of the vascular lumen (e.g., atherosclerosis) (Yurdagul Jr, Finney, Woolard, & Orr, 2016), and oxidative stress in inflammation (e.g., mitochondrial DNA damage due to mitochondrial oxidative stress) (Bonanni, Frazzini, Thomas, & Onofrj, 2015). These aging mechanisms, including chronic cerebral hypoperfusion, ischemia, and oxidative stress, eventually contribute to the pathogenesis of cognitive impairment and dementia (Yang et al., 2017). Fu et al. (2004) investigated the brain pathology related to cerebrovascular damage in 202 individuals with dementia from data obtained over 17 years and found that 45.5% of these individuals had cerebral atherosclerosis (Fu et al., 2004).

Reduced oxygenation related to cognitive decline in older adults is also associated with impairments in cardiopulmonary mechanics, which restrict oxygenation of the bloodstream and brain. Pulmonary function is particularly important because there is a nonlinear decrease in the relationship between age and pulmonary function from approximately 25 years of age (lung matures). The lungs suffer a stage of growth and maturation during human life and achieve maximal lung function about age 20 years in females and 25 years in males. After 50 years of age, the elastic fibers around the alveolar duct progressively degenerate, and induce enlargement of the airspaces, leading to increases in functional residual capacity (FRC) and residual volume (RV) in older adults. The key components of the respiratory system are the lungs, thoracic cage, and diaphragm. With aging, the thoracic cage is stiffened owing to the calcification of the rib cage. Moreover, osteoporosis-related kyphosis reduces the expansion of the thoracic cage during inspiration. Diaphragmatic strength also decreases with age due to muscle atrophy and age-related reduction of fast-twitch fibers and subsequently induces diaphragmatic fatigue and ventilatory failure in the respiratory system (Sharma & Goodwin, 2006). According to previous studies, several researchers have suggested a relationship between lower pulmonary function and increased risk of dementia hospitalization and cognitive decline through chronic hypoxia or the development of a pro-inflammatory state (Engstrom et al., 2002; Peers et al., 2009). Pulmonary function is mainly measured by forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV₁) using a spirometry method, and the data were standardized for age and sex (Sharma & Goodwin, 2006). Sachdev et al. (2006) studied the relationship between pulmonary function, brain anatomical parameters (e.g., ventricle-to-brain ratio [VBR] and white matter hyperintensity volume [WMHV]), and cognitive function in 469 adults (men = 252) aged 60–64 years. They revealed a significant relationship between FEV₁ and VBR in men, as well as between the FEV₁/FVC ratio and WMHV in both men and women. Hence, they suggested that FVC and FEV₁ could be significant predictors of VBR and indicators of brain atrophy and ultimately affect cognitive impairments in the mid-adult life (Sachdev et al., 2006). Moreover, a reduced pulmonary function may lead to decreased muscle mass and metabolic changes (Ceco, Weinberg, Chandel, & Sznajder, 2017; Gea, Casadevall, Pascual, Orozco-Levi, & Barreiro, 2012). This, in turn, further results in muscle atrophy and dysfunction (Mendes et al., 2015), thus, ultimately restricting functional activity (Belman, 1992). Identifying which aging-related pulmonary function is substantially associated with cognitive function and functional ability in older adults with dementia is currently of great interest. The aging-related pulmonary function include the progressive lowering of pulmonary function resulting from the impaired elastic fibers around the alveolar duct and reduced flexibility of the thoracic cage, as well as characteristic changes in diaphragmatic muscle fibers (Sharma & Goodwin, 2006). Dodd et al. (2015) demonstrated that there are relationships between pulmonary function and cognition in several studies, particularly in elderly groups. Pulmonary function was also related to functional limitations measured by six self-reported questions on physical function, such as basic mobility, in 3070 older adults (Gao et al., 2021). Additionally, Park, Lee, and Kang (2020) investigated the relationship between cognition, motor function, ADLs, and depression in older adults with dementia and found that cognition was associated with ADLs but not with depression. These previous studies have focused on the relationship between pulmonary function and cognitive or functional limitations as well as between cognition, motor function, ADLs, and depression in older adults with or without dementia (Dodd, 2015; Gao et al., 2021; Park, Lee, & Kang, 2020). Therefore, this study aimed to identify the relevance of aging-related pulmonary function on cognition, motor function, and ADLs in older adults with dementia.

2 Methods

2.1 Participants

Sixty-nine participants (> 60 years old) were recruited through a daycare center for patients with dementia. The sample size was determined according to the calculation method of Hulley et al. (2013) (Hulley, Cummings, Browner, Grady, & Newman, 2013) and derived from the insertion of the α (two-tailed) (0.05), power (0.95) or β (0.05), and expected correlation coefficient (0.50) values and ultimately calculated as 46 subjects. The inclusion criteria were as follows: (1) a diagnosis of dementia according to the Clinical Dementia Rating Scale (ICD-10), (2) a Korean version of the Mini-Mental State Examination (MMSE-K) score of < 19 points, and (3) ability to walk independently up to 15-meter with or without a walking aid (e.g., cane or walker). Participants were excluded if they had a history of stroke, neurological disorders, such as Parkinson’s or Huntington’s disease, orthopedic surgery within the last 2 years, psychiatric disorders, or severe communication problems (MMSE-K score of < 9 points). Participant characteristics are presented in Table 1. The experimental protocol complied with the Declaration of Helsinki and was approved by the Institutional Review Board of Woosuk University (WS-2019-14). Informed written consent was obtained from eligible participants and their family members before measurement.

Table 1
Demographic and clinical characteristics of participants

Characteristics Data (N = 69)

Age (years) 80.0±8.0^a

Height (cm) 157.6±9.6^a

Weight (kg) 56.3±14.7^a

Female/male, n (%) 41 (59.4)/28 (40.6)

Mini-Mental State 15.5±5.2^a

Examination (score)

Use of assistive device, n (%) 46 (66.7)

cane, n (%) 22 (31.9)

walker, n (%) 24 (34.8)

Hyperlipidemia, n (%) 3 (4.3)

Hypertension, n (%) 36 (52.2)

Diabetes, n (%) 20 (29.0)

Characteristics	Data (N = 69)
Age (years)	80.0±8.0^a
Height (cm)	157.6±9.6^a
Weight (kg)	56.3±14.7^a
Female/male, n (%)	41 (59.4)/28 (40.6)
Mini-Mental State	15.5±5.2^a
Examination (score)
Use of assistive device, n (%)	46 (66.7)
cane, n (%)	22 (31.9)
walker, n (%)	24 (34.8)
Hyperlipidemia, n (%)	3 (4.3)
Hypertension, n (%)	36 (52.2)
Diabetes, n (%)	20 (29.0)

Data are presented as mean±standard deviation^a. n: number of subjects.

2.2 Measurements

2.2.1 Aging-related pulmonary function measure

The FVC, FEV₁, and FEV₁/FVC ratio were measured to assess aging-related pulmonary function. The values were obtained by performing the FVC maneuver, according to the published 2019 guidelines for the standardization of spirometry (Graham, Steenbruggen, & Miller, 2019). FVC is the maximal volume of air expiration, starting from full inspiration with maximally forced effort (FVC maneuver). FEV₁ is the maximal volume of air exhaled in the first second of the FVC maneuver. A handheld spirometer (Pony Fx Cosmed, Italy) was used to measure pulmonary function variables, such as the FVC, FEV₁, and FEV₁/FVC ratio. The measurements were taken by trained and certified assessors. Participants underwent a least three trials of the FVC maneuver (and no more than eight trials) until two error-free reproducible data (FEV₁ and FVC within 5%) were obtained. The FVC (%) and FEV1 (%) were calculated by comparing the obtained values with the predicted values for healthy humans. These data were used in the analysis.

2.2.2 Cognitive function measure

The MMSE-K was developed to evaluate cognitive function (Baek, Kim, Park, & Kim, 2016). This assessment tool consisted of 30 subtitles on cognitive fields, including orientation (time and place), memory (registration and recall), attention and calculation, language function, and understanding and judgment. Scores (ranging from 0 to 30) were adjusted according to the patient’s level of education. A higher score indicates better cognitive function and a lower score indicates poor function (mild, 21–24; moderate, 10–20; severe, less than 10).

2.2.3 Motor function and ADLs measures

Motor function measures included the Berg balance scale (BBS), 10-meter walk test (10-MWT), and 6-minute walk test (6-MWT). The BBS is widely used to evaluate static and dynamic balance, and consists of a 14-item movement task scored on a five-level scale, from 0 (unable to perform) to 4 (able to perform). The maximum score is 56, and a higher score indicates good balancing ability (Muir-Hunter, Graham, & Montero Odasso, 2015; Telenius, Engedal, & Bergland, 2015). The 10-MWT is usually used to assess walking speed in meters per second (m/s) and is conducted on a straight 14-meter walking path. Measurements were recorded in the middle of the 10-meter path to exclude the effects of the acceleration and deceleration phases of walking (Kim, Park, Lee, & Lee, 2016). Participants were instructed to walk at their self-selected, comfortable pace, and fast pace, without running. The time required to walk the middle 10-meter was recorded using a stopwatch. Finally, the 6-MWT is a practical and reliable test that reflects the physical functional capacity (or exercise capacity and motor function) of patients with a variety of cardiopulmonary diseases (Rikli & Jones, 1998). It was performed indoors on a straight 30-meter walking path, marked at every 1 meter. The participants were instructed to walk repeatedly between the bilateral end line of 30 meters for 6 min without running. For ADLs assessment, the modified Barthel index (MBI) is often used to measure the level of functional independence in ADLs. This measure consists of 10 sub-items: feeding, personal hygiene, bathing, dressing, toilet transfer, bladder control, bowel control, chair/bed transfers, stair climbing, and ambulation. The scores ranged between 0 to 100. A higher score represents a higher level of functional independence in performing basic ADLs (Leung, Chan, & Shah, 2007).

2.3 Data analysis

Descriptive statistics are presented as mean and standard deviation. Pearson’s product correlation coefficient (r) was used to investigate the correlation between aging-related pulmonary function (FVC, FEV₁, and FEV₁/FVC), cognition (MMSE-K), motor function (BBS, 10-MWT, and 6-MWT), and ADLs (MBI). A range of r values of 0.70–1.00 indicates a very strong or strong correlation; 0.40–0.69 indicates moderate correlation; 0.10–0.39 indicates a weak correlation; < 0.1 was considered negligible (Schober, Boer, & Schwarte, 2018). Statistical Package for the Social Sciences (SPSS) for Windows version 23.0 (SPSS Inc., Chicago, IL, USA) was used for statistical analyses. Statistical significance level was set at p < 0.05.

3 Results

Table 2 shows the correlations of aging-related pulmonary function (FVC, FEV₁, and FEV₁/FVC ratio) with cognition (MMSE-K), motor function (BBS, 10-MWT, and 6-MWT), and ADLs (MBI). FVC (r = 0.483, p = 0.002) and FEV₁ (r = 0.512, p = 0.001) were positively correlated with 6-MWT. However, FVC and FEV₁ were not correlated with other mea-sures, including MMSE-K (r = 0.272 and 0.140, p = 0.098 and 0.409), BBS (r = 0.147 and 0.183, p = 0.378 and 0.279), 10-MWT (r = 0.173 and 0.276, p = 0.299 and 0.098), and MBI (r = 0.267 and 0.027, p = 0.105 and 0.874, respectively). Additionally, the FEV₁/FVC ratio was not significantly correlated with MMSE-K (r = 0.180, p = 0.221), BBS (r = 0.197, p = 0.180), 10-MWT (r = 0.228, p = 0.118), 6-MWT (r = 0.136, p = 0.366), and MBI (r = 0.054, p = 0.717) (Table 2).

Table 2
Correlations between aging-related pulmonary function, cognition, motor function, and ADLs measures

FVC (%) FEV₁ (%) FEV₁/FVC ratio

MMSE-K 0.272 (0.098) 0.140 (0.409) 0.180 (0.221)

BBS 0.147 (0.378) 0.183 (0.279) 0.197 (0.180)

10-MWT 0.173 (0.299) 0.276 (0.098) 0.228 (0.118)

6-MWT 0.483 (0.002)^† 0.512 (0.001)^† 0.136 (0.366)

MBI 0.267 (0.105) 0.027 (0.874) 0.054 (0.717)

	FVC (%)	FEV₁ (%)	FEV₁/FVC ratio
MMSE-K	0.272 (0.098)	0.140 (0.409)	0.180 (0.221)
BBS	0.147 (0.378)	0.183 (0.279)	0.197 (0.180)
10-MWT	0.173 (0.299)	0.276 (0.098)	0.228 (0.118)
6-MWT	0.483 (0.002)^†	0.512 (0.001)^†	0.136 (0.366)
MBI	0.267 (0.105)	0.027 (0.874)	0.054 (0.717)

Data are Pearson correlation coefficient (P) values, ^†p < 0.01. MMSE-K: Mini-Mental State Examination (Korean version), BBS: Berg balance scale, 10-MWT: 10-meter walk test, 6-MWT: 6-minute walk test, MBI: modified Barthel index, FVC: Forced vital capacity, FEV₁: Forced expiratory volume in 1 second.

Correlations between cognition (MMSE-K), motor function (BBS, 10-MWT, and 6-MWT), and ADLs (MBI) are presented in Table 3. MMSE-K was positively correlated with BBS (r = 0.283, p = 0.022) and MBI (r = 0.454, p = 0.000). BBS was positively correlated with 10-MWT (r = 0.575, p = 0.000), 6-MWT (r = 0.561, p = 0.000), and MBI (r = 0.628, p = 0.000). Additionally, 10-MWT was positively correlated with 6-MWT (r = 0.671, p = 0.000) and MBI (r = 0.425, p = 0.000). The relationship between the 6-MWT and MBI revealed a moderate positive correlation (r = 0.468, p = 0.000) (Table 3).

Table 3

Correlations between motor function and ADLs measures

	BBS	10-MWT	6-MWT	MBI
MMSE-K	0.283 (0.022)^*	0.004 (0.974)	0.171 (0.183)	0.454 (0.000)^†
BBS	–	0.575 (0.000)^†	0.561 (0.000)^†	0.628 (0.000)^†
10-MWT	–	–	0.671 (0.000)^†	0.425 (0.000)^†
6-MWT	–	–	–	0.468 (0.000)^†

Data are Pearson correlation coefficient (P) values, ^*p < 0.01, ^†p < 0.01. MMSE-K: Mini-Mental State Examination (Korean version), BBS: Berg balance scale, 10-MWT: 10-meter walk test, 6-MWT: 6-minute walk test, MBI: Modified Barthel index.

4 Discussion

To the best of our knowledge, this study is the first to report the relationship between aging-related pulmonary function, cognition, motor function, and ADLs in older adults with dementia. Importantly, aging-related pulmonary function, measured by FVC and FEV₁, was closely related to physical functional capacity (6-MWT), but not to other parameters of motor function, cognition, and ADLs. Cognitive function was only associated with balance and the ADLs. Moreover, significant relationships between all measures of balance, walking speed, physical functional capacity, and functional independence in ADLs were revealed. These findings demonstrated that aging-related pulmonary function had at least some independent association with motor function in older adults with dementia.

In the relationship between aging-related pulmonary function and physical functional capacity, positive relationships between FVC and FEV₁ and 6-MWT indicated that poor pulmonary function was closely related to a decline in physical functional capacity or walking tolerance in older adults with dementia. The 6-MWT is a simple test that evaluates system responses involved in walking tole-rance, including the pulmonary system, systemic circulation, and blood and muscle metabolism (Garcia-Aymerich, Lange, Benet, Schnohr, & Antó, 2006; test, 2002). Agrawal and Awad (2015) reported that 6-MWT was significantly correlated with FVC (r = 0.260) and FEV₁ (r = 0.367) in 102 patients with chronic obstructive pulmonary disease (COPD) and 58 patients with chronic lung disease. Another previous study demonstrated that the 6-MWT in patients with severe and very severe COPD had positive correlations with FEV₁(r = 0.47 and 0.59) and FEV₁/FVC (r = 0.42 and 0.52), respectively (Chen et al., 2012). Moreover, Patel (2015) found that in 50 patients with COPD, FVC was significantly correlated with 6-MWT, with a p-value of 0.038, while FEV₁ was not (p= 0.074). Most previous studies have shown that the correlation analysis between pulmonary function and physical functional capacity was mainly performed patients with COPD (Agrawal & Awad, 2015; Chen et al., 2012; Patel, 2015). To our knowledge, no article has published data on the correlation analysis of older adults with and without dementia. Therefore, the present study is the first to show the relationship between aging-related pulmonary function and physical functional capacity in older adults with dementia. In this finding, we suggest that in older adults with dementia, the reduced pulmonary function was unable to walk for longer distance.

In the relationship of aging-related pulmonary function with cognitive and motor functions (except for 6-MWT) and ADLs, our results showed no significant association between FVC, FEV1, and FEV1/FVC ratio and MMSE-K. These findings are inconsistent with those of previous studies on the correlation between pulmonary function and cognition. Several studies have demonstrated a few independent associations between pulmonary function and cognition (Vidal et al., 2013; Weuve et al., 2011). Weuve et al. (2011) demonstrated through a prospective observational study (N = 864, 12-year follow-up) that higher FEV₁ was related only to a slower deterioration in attention, whereas the rate of FEV₁ decline was not related to cognition (Weuve et al., 2011). In a prospective population-based cohort study (N = 3,635), reduced pulmonary function (FEV₁) in midlife predicted slower speed of processing, impaired memory and executive function, and greater possibility of cognitive impairment or dementia 23 years later. In contrast, a reduction in pulmonary function over 7.8 years in midlife was not related to cognitive impairment or dementia (Vidal et al., 2013). According to these studies (Vidal et al., 2013; Weuve et al., 2011), the overall evidence on the relationship between FEV₁ and cognitive function is limited (Dodd, 2015). In the present study, aging-related pulmonary function parameters were not significantly different among ADLs and motor function measures, such as BBS and 10-MWT. These results are difficult to compare with previous studies because these were not studied in older adults with or without dementia. However, several studies have investigated the bidirectional relationship between pulmonary function and physical activity in large samples (Bédard et al., 2020; Gao et al., 2021; Pelkonen et al., 2003). Bédard et al. (2020) found that FVC and FEV₁ were inversely correlated with functional limitation measured by six self-reported questions on physical function in 3070 older adults. Pelkonen et al. (2003) demonstrated that a high physical activity level was related to a slower decline in pulmonary function and lower mortality, suggesting that middle-aged and older adults are encouraged to perform high levels of physical activity or exercise.

With regard to the relationship between cognition and motor function or ADLs, significant relationships between MMSE-K and BBS or MBI showed that cognitive dysfunction was found to affect impaired balance and ADLs in older adults with dementia, which was supported by previous studies (Lee, 2020; Park, Lee, & Kang, 2020). Lee (2020) demonstrated that the MMSE was positively correlated with the BBS (r = 0.338) and MBI (r = 0.363) in 63 individuals with mild-to-moderate Alzheimer’s disease dementia. Moreover, Park, Lee, and Kang (2020) reported a significant correlation between MMSE-K and MBI (r = 0.486) in 74 individuals with dementia. Based on our findings, we suggest that appropriate physical activity through changes in intervention intensity and time is closely related to health care management in individuals with dementia.

Although our study has shown meaningful results, it has a few limitations that should be considered in future research. First, our data were measured and assessed by two examiners who collected blinded data. Further research should be conducted among several examiners (more than two examiners). Second, the MMSE-K is a cognitive screening test com-monly used to assess general cognitive function. Hence, if a more sensitive assessment tool, such as the Montreal Cognitive Assessment is used, more informative results may be obtained. Finally, the present study was cross-sectional in design, which cannot confirm a causal relationship between aging-related pulmonary function, cognition, and functional status in older adults with dementia. In future research, regression analyses using a larger sample should be performed to evaluate the predictive value of these factors.

5 Conclusion

Aging is associated with cerebrovascular dysfunction and physiological changes, such as reduced pulmonary function. These changes can eventually induce cognitive impairment or dementia. Reduced lung function may lead to a decline in muscle mass and changes in metabolism, which in turn, may induce muscle atrophy and dysfunction, and ultimately inhibit functional ability. In summary, our findings showed that the aging-related pulmonary function, as measured by FVC and FEV₁, were related only to 6-MWT in physical functional capacity, which means that in older adults with dementia, the reduced pulmonary function was unable to walk for longer distance. Significant relationships between MMSE-K and BBS or MBI showed that cognitive dysfunction was found to affect impaired balance and ADLs. Based on our findings, appropriate physical activity through changes in intervention intensity and time is closely related to health care management in individuals with dementia.

Conflict of interest

None to report.

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